EXPERIENCE WITH SURVEILLANCE, PERCEIVED THREAT OF SURVEILLANCE, SNS POSTING BEHAVIOR, AND IDENTITY CONSTRUCTION ON SNSs: AN EXAMINATION OF CHINESE COLLEGE STUDENTS IN THE U.S.
Kisun Kim
A Thesis
Submitted to the Graduate College of Bowling Green State University in partial fulfillment of the requirements for the degree of
MASTER OF ARTS
August 2016
Committee:
Sung-Yeon Park, Advisor
Gi Woong Yun
Louisa Ha © 2016
Kisun Kim
All Rights Reserved iii
ABSTRACT
Sung-Yeon Park, Advisor
This study applied the uses and gratifications (U&G) perspective in order to explore
Chinese students’ SNS (Social Networking Site) identity construction in four ways: (1) how
Chinese young adults studying in the U.S. use various kinds of SNSs, (2) how their use of SNSs are influenced by the surveillance of the Chinese government, (3) how their experience with and perceived threat of surveillance varies depending on the type of SNS being used, and (4) how their experience with and perceived threat of surveillance are related to their SNS posting
behaviors and identify construction on SNSs.
This study categorized SNSs by their national origin (Chinese SNSs vs. U.S. SNSs) and by their network openness (open SNSs vs. closed SNSs). Thus, SNSs were assigned to one of the four categories: (1) Chinese open SNSs, (2) Chinese closed SNSs, (3) U.S. open SNSs, and (4)
U.S. closed SNSs.
169 Chinese students attending colleges in the U.S. participated in a survey for this study.
They were asked about their experience with and perceived threat of surveillance, posting behaviors, and identify construction on the four different types of SNSs.
This study found that Chinese students in the U.S. have different experiences and perceptions of surveillance depending on the type of SNS they use. This study also found that the different level of surveillance experience and perceived threat of surveillance were related to different SNS posting behaviors and identity construction strategies. Implications of these findings are discussed, and limitations and opportunities for future research are addressed. iv
This thesis is dedicated to my parents who pray every day for me. v
ACKNOWLEDGMENTS I would like to thank numerous people both academically and personally for their support
and assistance in making this thesis in a reality.
My advisor, Dr. Park, deserves my deepest gratitude for her willingness to assist me in every way possible. She is the best person I had ever had academically as well as personally. It is not exaggeration that “perfect” is the word for her. I, really, appreciate her carefulness and thoughtfulness. If she were not my advisor, I could not succeed this long and tough journey.
My genuine thanks also go to Dr. Yun for his valuable examination of this study. His interest and encouragement influence me to study this research. He helped me to effectively conceptualize various ideas I had about this study. Without them, I would not have been able to complete the study.
I am also incredibly grateful to Dr. Ha for her careful critiques and specific suggestions, which refined and improved my thesis. Being a member of her research team, moreover, I got many research experiences.
I would like to express my appreciation to Claire. I have depended on her for my two academic years. I know she had a lot of difficulty and hardness on her life because she is also an international doctoral student. Nevertheless, she always tried to care about me, and paid attention to my situations. I cannot imagine my two years life here without her.
I am also grateful to all of Chinese students who participated in this study. Even though the questionnaire was longer than normal questionnaire, a number of Chinese students participated in this study. Their concern and interest about this study encouraged me to keep my work. Especially, I wish to express my heartfelt gratitude to Qiusi, Sima, Dandan, and Yihui for their valuable help and encouragement. vi
Without my friends’ help, this process would have been much too difficult of an adventure. I especially would like to thank my friends Cindy, Starry, Dai, Olivia, Emi, Sasha,
Fang, Scott, CT, Cody, Ben, and Chenjie. A special thanks to my friend Courtney Wright.
Finally, I would like to say that my parents and brother. They always support me whatever I want to do. Their pray, devotion, continual support, unlimited faith, and love in my own potential makes me being a very precious and treasure honor. vii
TABLE OF CONTENTS
Page
CHAPTER I. INTRODUCTION ...... 1
Organization of the Thesis ...... 4
CHAPTER II. LITERATURE REVIEW ...... 5
Internet Surveillance in China ...... 5
Uses and Gratifications (U&G) Perspective ...... 8
Uses and Gratifications (U&G) Perspective on Social Networking Sites ...... 10
Motivation for SNS Use ...... 11
Identity Construction through SNS Use ...... 13
Different Functions and Motivations, Different Social Networking Sites ..... 15
CHATPER III. RESEARCH HYPOTHESES ...... 19
Experience with Surveillance on Different SNSs ...... 21
Perceived Threat of Surveillance on Different SNSs ...... 22
Experience with Surveillance, Perceived Threat of Surveillance, and SNS Posting
Behaviors ...... 22
Predictors of Identity Construction on SNSs ...... 24
CHAPTER IV. METHOD ...... 26
Procedure ...... 26
Participants ...... 27
Measurement ...... 27
Experience with surveillance (ES) ...... 27
Perceived threat of surveillance (PTS) ...... 28 viii
Political Posting (PP) ...... 30
Social Criticism (SC) ...... 30
Privacy Protection Behavior (PPB) ...... 30
Private Information Disclosure (PID) ...... 31
SNS Types ...... 32
Demographic Variables ...... 32
Strategies for Statistical Analysis ...... 33
CHAPTER V. RESULTS ...... 35
Descriptive Results ...... 35
Basic Demographic Characteristics of the Participants ...... 35
SNS Accounts ...... 39
Descriptive Statistics for Each SNS ...... 41
Experience with Surveillance ...... 43
Perceived Threat of Surveillance ...... 43
Political Posting ...... 44
Social Criticism ...... 45
Privacy Protection Behavior ...... 46
Private Information Disclosure ...... 47
Result of Hypotheses ...... 48
Experience with Surveillance on Different Types of SNSs ...... 48
Perceived Threat of Surveillance on Different Types of SNSs ...... 50
Relationship between Experience with Surveillance and Posting Behaviors 53
1. Chinese SNSs ...... 53 ix
Political posting ...... 53
Social criticism ...... 54
2. US SNSs...... 55
Political posting ...... 55
Social criticism ...... 56
3. Open SNSs ...... 57
Political posting ...... 57
Social criticism ...... 58
4. Closed SNSs...... 58
Political posting ...... 59
Social criticism ...... 60
Relationship between Experience with Surveillance and Identity Construction
...... 60
1. Chinese SNSs ...... 61
Political posting ...... 61
Social criticism...... 61
2. US SNSs ...... 62
Political posting ...... 62
Social criticism...... 63
3. Open SNSs ...... 64
Political posting ...... 64
Social criticism...... 64
4. Closed SNSs ...... 65 x
Political posting ...... 65
Social criticism ...... 66
Predictors of Privacy Protection Behaviors ...... 66
1. Chinese SNSs ...... 67
2. US SNSs...... 68
3. Open SNSs ...... 69
4. Closed SNSs...... 70
Predictors of Privacy Protection Behaviors ...... 71
1. Chinese SNSs ...... 71
2. US SNSs ...... 72
3. Open SNSs ...... 73
4. Closed SNSs ...... 74
CHAPTER VI. DISCUSSION ...... 76
Limitations ...... 79
REFERENCES ...... 81
APPENDIX A. HSRB APPROVAL ...... 89
APPENDIX B. INVITATION EMAIL TO PRESIDENT OF CHINESE STUDENTS
ASSOCIATION ...... 90
APPENDIX C. INVITATION EMAIL TO STUDENTS ...... 91
APPENDIX D. INFORMED CONSENT...... 92
APPENDIX E. QUESTIONNAIRE ...... 94 xi
LIST OF FIGURES
Figure Page
1 A Four Different Types of SNSs by National Origin and Network Openness. 20
2 Research Model: Experience with Surveillance, Perceived Threat of Surveillance,
Posting Behaviors, and Identity Construction ...... 25
3 Four Categories of Popular SNSs among Chinese Students in the U.S...... 32 xii
LIST OF TABLES
Table Page
1 Reliability Coefficients of Experience with Surveillance ...... 28
2 Reliability Coefficients of Perceived Threat of Surveillance ...... 29
3 Reliability Coefficients of Privacy Protection Behavior ...... 31
4 Descriptive Statistics for Sex ...... 35
5 Descriptive Statistics for U.S Degree Programs Enrolled ...... 36
6 Descriptive Statistics for Age ...... 37
7 Descriptive Statistics for Geographic Origin ...... 38
8 Descriptive Statistics for Prior Experience with US SNSs ...... 38
9 Descriptive Statistics for the Duration of Residency in the U.S ...... 39
10 Descriptive Statistics for SNS Accounts and Regularly used SNSs ...... 41
11 Descriptive Statistics for the Usage Rates (Time/Visit) of Regularly Used
SNSs ...... 43
12 Means and Standard Deviations on the Measure of Politic Posting on Different
Types of SNSs ...... 45
13 Means and Standard Deviations on the Measure of Social Criticism on
Different Types of SNSs ...... 46
14 Means and Standard Deviations on the Measure of Privacy Protection
Behavior on Different Types of SNSs ...... 47
15 Means and Standard Deviations on the Measure of Private Information
Disclosure on Different Types of SNSs ...... 48
16 Group Differences for Experience with Surveillance between Chinese SNSs xiii
and US SNSs ...... 49
17 Group Differences for Experience with Surveillance between Open SNSs
and Closed SNSs ...... 49
18 Group Differences for Experience with Surveillance among Four Different
Types of SNSs ...... 50
19 Group Differences for Perceived Threat of Surveillance between Chinese
SNSs and US SNSs ...... 51
20 Group Differences for Perceived Threat of Surveillance between Open SNSs
And Closed SNSs ...... 52
21 Group Differences for Perceived Threat of Surveillance among Four Different
Types of SNSs ...... 52
22 One-Way Analysis of Variance for the Relationship between Experience
with Surveillance and Political Posting on Chinese SNSs ...... 54
23 One-Way Analysis of Variance for the Relationship between Experience
with Surveillance and Social Criticism on Chinese SNSs ...... 55
24 One-Way Analysis of Variance for the Relationship between Experience
with Surveillance and Political Posting on US SNSs ...... 56
25 One-Way Analysis of Variance for the Relationship between Experience
with Surveillance and Social Criticism on US SNSs ...... 57
26 One-Way Analysis of Variance for the Relationship between Experience
with Surveillance and Political Posting on Open SNSs ...... 58
27 One-Way Analysis of Variance for the Relationship between Experience
with Surveillance and Social Criticism on Open SNSs ...... 58 xiv
28 One-Way Analysis of Variance for the Relationship between Experience
with Surveillance and Political Posting on Closed SNSs ...... 59
29 One-Way Analysis of Variance for the Relationship between Experience
with Surveillance and Social Criticism on Closed SNSs ...... 60
30 One-Way Analysis of Variance for the Relationship between Perceived
Threat of Surveillance and Political Posting on Chinese SNSs ...... 61
31 One-Way Analysis of Variance for the Relationship between Perceived
Threat of Surveillance and Social Criticism on Chinese SNSs ...... 62
32 One-Way Analysis of Variance for the Relationship between Perceived
Threat of Surveillance and Political Posting on US SNSs ...... 63
33 One-Way Analysis of Variance for the Relationship between Perceived
Threat of Surveillance and Social Criticism on US SNSs ...... 63
34 One-Way Analysis of Variance for the Relationship between Perceived
Threat of Surveillance and Political Posting on Open SNSs ...... 64
35 One-Way Analysis of Variance for the Relationship between Perceived
Threat of Surveillance and Social Criticism on Open SNSs ...... 65
36 One-Way Analysis of Variance for the Relationship between Perceived
Threat of Surveillance and Political Posting on Closed SNSs ...... 66
37 One-Way Analysis of Variance for the Relationship between Perceived
Threat of Surveillance and Social Criticism on Closed SNSs ...... 66
38 Summary of Hierarchical Regression Analysis for Variables Predicting PPB
on Chinese SNSs ...... 67
39 Summary of Hierarchical Regression Analysis for Variables Predicting PPB xv
on US SNSs ...... 68
40 Summary of Hierarchical Regression Analysis for Variables Predicting PPB
on Open SNSs ...... 69
41 Summary of Hierarchical Regression Analysis for Variables Predicting PPB
on Closed SNSs ...... 70
42 Summary of Hierarchical Regression Analysis for Variables Predicting PID
on Chinese SNSs ...... 72
43 Summary of Hierarchical Regression Analysis for Variables Predicting PID
on US SNSs ...... 73
44 Summary of Hierarchical Regression Analysis for Variables Predicting PID
on Open SNSs ...... 74
45 Summary of Hierarchical Regression Analysis for Variables Predicting PID
on Closed SNSs ...... 75 1
CHAPTER I. INTRODUCTION
The number of users of Social Networking Sites/Services (SNSs) has been increasing and
SNSs have become one of primary means of communication (Gao, 2016). The various
communicative functions of social media outlets such as Facebook and Twitter have attracted
millions of users and many of them, especially younger people, have integrated their daily lives
and feelings to these sites (Ellison, 2007). Through SNSs, users not only maintain the
relationship with their friends in real life, but also make new friends online (Bumgarner, 2007;
Park et al., 2009). Moreover, SNS users can get information from others, or share knowledge
with others through SNSs (Bumgarner, 2007). In addition to using these interpersonal
communicative functions, users can construct their identity in SNSs by posting pictures on their
profile and disclosing personal information such as favorite movies, music, and TV shows
(Barker, 2009).
Not all countries, however, allow their citizens unrestricted access to SNSs. China, along
with a few other countries such as North Korea and Iran, bans citizens from using SNSs that are
originated from foreign countries (Ai, 2013). As part of restriction on people’s access to U.S.
websites (Zhang & Lin, 2014), the Chinese government has been forcing its citizens to use only
SNSs engendered by Chinese companies such as Weibo and Renren.
While blocking Chinese Internet users’ access to SNSs from other countries and a variety of other overseas web content, the Chinese government has been conducting a comprehensive surveillance and censoring program as well (Ai, 2013). Through the “Great Firewall,” a national
Internet filtering system, the Chinese government filters and censors content generated by SNS users, especially content regarding sensitive topics about the Chinese government and social issues. 2
The subjects falling under the government surveillance are not strictly limited to political issues. Recently, an SNS post generated by Papi Jiang, a popular online star, was censored by the
Chinese government (Meng, 2016). Her content mostly talked about young women’s marriage, careers, and romantic relationships. In commenting on the topics, she called herself a “leftover woman,” a new sociological term referring to highly educated single women over 30 years of age.
Even though her post was not directly related to sensitive political issues (e.g., human rights, inequality, etc.), her video was removed from Weibo.
To avoid the risk of censorship, Chinese SNS users often do not reveal their true name and personal information. They also avoid expressing their thoughts or arguments about political issues, even though SNSs are meant to be a place to freely express their personal identity and discuss various issues with other people. For example, 62% of Chinese Internet users do not expose their true identity on SNSs (Freedom house, 2015). In an interview (Ai, 2013), almost every interviewee staying in New Zealand answered that they considered surveillance by the
Chinese government when posting or revealing their personal information on SNSs. With worries about surveillance, behaviors and activities online were influenced by the recognition of censorship.
Then, a question arises regarding Chinese people who can have access to non-Chinese
Social Media. Since the Chinese government does not ban Chinese citizens from visiting or living in other countries, Chinese people outside of their country can freely access the websites of other countries. For example, Chinese people living in the U.S. can use both kinds of SNSs,
China-based SNSs and U.S.-based SNSs, on which they might have different levels of surveillance experience and perception. Based on the different experiences and perceptions about
3 surveillance, their identity management and posting behavior on China-based and U.S.-based
SNSs can be different as well.
Not only the national origin of SNSs, Moreover, but openness of SNSs could lead to different experience and perception about surveillance. Especially, Chinese students’ SNS behaviors could be different depending on the level of openness. For example, they could be more reluctant to say sensitive issue on public place than private place since they might be worried about the surveillance of the Chinese government.
Drawing from the theoretical framework of Uses and Gratifications, this research examines how Chinese SNS users living in the U.S. have different experiences and perceptions about SNSs based on the national origin and openness of the SNSs. Furthermore, this study connects Chinese students’ experiences with surveillance and perceived threat of surveillance to their SNS posting behaviors and identity construction. More specifically, in this study, SNSs commonly used by Chinese people living in the U.S. were classified by two attributes that could affect their experiences and perceptions of surveillance: national origin (China vs. U.S.) and openness (open vs. closed). By combining these two attributes, four categories were created:
Chinese open SNSs, Chinese closed SNSs, US open SNSs, and US closed SNSs. In sum, this study examines whether Chinese students’ experiences with surveillance and perceived threat of surveillance are different depending on the different types of SNSs. Additionally, it will examine whether Chinese students in the U.S. make distinctions across different types of SNSs when posting political comments and providing personally identifying information.
This study has an implication in that it looks into Chinese students’ experience and perception depending on different types of SNSs in different situation. Also, this study shed lights on the quantitative finding about Chinese students’ experience with and perception of
4 surveillance, and the relationship between Chinese students’ experience with and perception of surveillance and SNS identity construction.
Organization of the Thesis
This thesis comprises six chapters:
Chapter I presented the introduction. This chapter introduced general information about
Chinese censorship and SNS users’ behaviors.
Chapter II was the literature review and theoretical background. This chapter explained
Chinese government’s surveillance with more depth and concentrated on how people use SNSs based on the Uses and Gratifications perspective.
Chapter III presented research hypotheses. Also contained in this chapter are the definitions of major terms.
Chapter IV presented method. This chapter addressed the method of this study, as well as how the survey questionnaires were constructed.
Chapter V reported the results from data analysis, including preliminary analyses and the testing of hypotheses.
Chapter VI discussed the results and interpreted the findings. This chapter also suggested directions for future research and pointed out the limitations of this study for future endeavors.
References and appendices were provided at the end of this manuscript.
5
CHAPTER II. LITERATURE REVIEW
Internet Surveillance in China
The number of social media users has increased at a rapid rate throughout the world.
More and more people stay on social networking sites to keep relationships, get information, and do other activities. Between 2010 and 2016, SNS users worldwide increased from 97 million to
2.22 billion and the figure is expected to reach 2.72 billion by 2018 (Statista, 2016a). Of the 2.2 billion people who have a social media account, approximately 1.7 billion people are actively using social networking sites (Rosen, 2016).
China is no exception. China’s SNS scene is the largest across the world (Statista, 2016a) and social media use among Chinese individuals is consistently growing. The population of
Internet users in China is 650 million, almost twice the population of U.S. Internet users.
According to Statista (Statista, 2016b), the number of Chinese Internet user would increase to
504 million by 2018 and it expects 62 percent of Chinese Internet users would use SNSs by 2018
(Statista, 2016c). Moreover, the vast majority of Chinese people who identified themselves as social media users are considered active users (Jamie, 2015).
In spite of all these impressive numbers and even grander projections, Chinese people’s
SNS usage has one serious limitation: The government controls their content in many ways. For example, 12 government agencies in China, including General Administration of Press and
Publication (GAPP), the state Council Information Office (SCIO), and the State Administration of Radio, Film and Television (SARFT), are related to censorship of the Internet, even though their power and influence varies (Zhao, 2009). It is common knowledge that the government uses filtering systems to block its citizens’ access to certain contents. 6
It was 1996 that the censorship practice was first announced (Zhao, 2009). As time passed, the Chinese government elaborated much on specific regulations to restrict foreign interferences in its domestic policies and their enforcements. The Chinese government announced that they would censor to prevent spreading rumors or harmful information against the country’s government (Zhao, 2009). After a few high-profile protests by ethnic/religious minority groups such as the Uyghur and Muslims, the Chinese government introduced a regulation that blocked some specific SNSs (Jamie, 2015).
Granted, monitoring and filtering of online content also takes place in other countries that claims to have freedom of speech online (Heyes, 2015). For example, online child pornography is regulated in many countries, including the U.S. (Akdeniz, 1997). Also, Google, an American multinational technology company, is often criticized for screening some specific information such as banning payday loans from its advertising system to protect consumers (Rosen, 2013).
Even though the Chinese government claims its purpose is to unify their citizens and the country, it could restrict Internet users’ behaviors and free speech online. Given the rate of surveillance, online freedom of expression in China appears to be exceptionally limited compared to other countries. According to a study titled “Freedom on the Net 2015,” internet users in China are afforded by far the least freedom of information (Freedom house, 2015).
Broadly speaking, the Chinese government’s surveillance program is implemented in two ways. The first way the Chinese government controls its citizens’ use of the Internet is to block off specific websites. This prevents Chinese Internet users from accessing websites originating from overseas as well as other domestic websites deemed harmful to the government of China.
The “Golden Shield” or “Great Firewall of China” is a widely known system for surveillance and censorship by the Chinese Ministry of Public Security (MPS) (Freedom house, 2015). Included 7 in the list of websites banned by the program are many US-originated SNSs and search engine pages such as Google, Yahoo, Facebook, and Twitter (Liang &Lu, 2010; Mackinnon, 2008;
Ramzy, 2016).
The second way the Chinese government controls its citizens’ Internet use is to block specific keywords. For example, if a Chinese citizen is looking for information containing such words as “persecution,” “democracy movements,” and “Tibetan independence” a blank screen would come on saying this link is not available (Wiseman, 2008). King and others (2013) pointed out that, the Chinese government filters 236 words, and almost every item is associated with social issues or politics (King et al., 2013).
In order to censor the vast amount of online content effectively, the Chinese government makes each online social network company censor user-generated content on their own network.; hence, the large number of providers entrusted with the right from the Chinese government to have censored and monitored internet content generated by Internet users (King et al., 2013).
When those domestic sites fail to censor as required, they would be penalized such as being fined, or shutting down (Qiu, 1999). To avoid the fines or, even worse, being shut down by the Chinese government, Chinese SNS companies employ hundreds of people to monitor the content of their
SNSs uploaded by users (King et al., 2013). According to an estimate, SNS companies each hire between 20,000 and 50,000 employees for the purpose alone and many of them are low-ranking party members at various government offices (King et al., 2013).
Beyond censoring what the public post on the Internet, the Chinese government also proactively manage the web by preserving and producing content that is favorable toward the party and its policy (lam, 2012). They hire a large yet undisclosed number of people to upload posts and other content to the web to shape public opinion. Those who create web content 8 favorable to the party in exchange for payment are called by critics as the “50-cent party,” referring to the unconfirmed rate of 50 cents-per-comment they are paid for posting such comments (King et al., 2016). They often label people who criticize their government as traitors of the country (Lam, 2012).
Ironically, the attitude of Chinese people toward the surveillance by their government is not entirely negative. According to a survey conducted with a group of respected Chinese academics (Pew, 2008), almost 80% of the respondents answered that their government were entitled to conduct online surveillance. Supporting the Chinese government’s surveillance, for example, an interviewee named Jong Ju said that everyone has a right to say anything if they want to in an ideal world, however, if individuals said anything they wanted to say online in the real world, it would be confusing and harmful to the society (Sydell, 2008).
Even though some Chinese SNS users acknowledge that censorship is not good they think they cannot do anything about it. Instead of resisting the government pressure to watch what they say online, they think it is inevitable to adapt to it. For example, Ema (2012) posts on her blog about the 50-cent Party online, “I also used to curse the 50-centers, but now I find that such reaction is too naïve: They are just by-products of the corrupted social system.”
Uses and Gratifications (U&G) Perspective
The uses and gratifications (U&G) perspective is a classic theoretical framework that allows researchers to examine people’ media behavior and motivation (Katz et al, 1959).
Contrary to the established belief of early media scholars that the media directly influences individuals’ attitudes, opinions, and behaviors, U&G assumes that people play a more active role in shaping and constructing their views by adopting or rejecting social standards or norms from the mass media (McQuail & Windahl, 2015). Moreover, U&G allows scholars to shift away
9
from questions such as “What does the media do to people?” and toward questions like, “What do people do with the media?” (Katz, 1959; McQuail & Windahl, 2015; Ruggiero, 2000). In other words, U&G allowed researchers to escape some of the problems of the media effects paradigm.
The U&G perspective emphasizes that people obtain gratifications by selecting specific media and media content among diverse types of media and a wide range of media content. The act of media selection satisfies individuals’ social and psychological needs. This is because media audiences are regarded as active, discerning, and motivated individuals who are goal- directed in their media use (Allport & Cantril, 1935; Quan-Haase & Young, 2010). For example, when people have a motivation to gain information from the media, specific media and media content are selected to gratify this need (Quan-Haase & Young, 2010).
In current U&G research, there are five key assumptions. First, communication behavior is motivated, goal-directed, and purposive. People deliberately and intentionally select the media and media content. Second, the media users are not passive but active, and thus they choose which media they would use based on their needs. Third, people are not completely cut off from the influence of society and environment. There are many elements that shape people’s expectations about media and media content. Fourth, the media consistently struggle to hold a dominant position against other communication forms such as interpersonal interaction. Finally, people are affected more by their own motives than by the media (Bryant & Oliver, 2009).
Based on previous research, the needs of media users can be categorized into four types:
1) “emotional needs,” associated with enhancing aesthetic and emotional experience; 2)
“cognitive needs,” associated with enhancing information, knowledge, and understanding; 3)
“social needs,” associated with enhancing contact with family, friends, and the world; 4) 10
“habitual needs,” associated with manneristic activities such as making background noise (Wang
& Tchemev, 2012). Alternatively, McQuail (2015) summarized the motivations for media use into four types: 1) “information,” related to seeking information; 2) “entertainment,” related to having fun; 3) “social interaction” related to connecting with others; 4) “personal identity,” related to constructing and creating themselves (McQuail, 2015).
Uses and Gratifications (U&G) Perspective on Social Networking Sites
Even though many researchers had shed light on the importance of the U&G perspective before, the significance of this theory resurged with the emergence of the Internet and the development of computer-mediated communication. Especially, as SNSs with interactive features became popular in the world, the concept of “active users,” the core notion of the U&G perspective, is strengthened and fortified in the current SNS environment (Ruggiero, 2000).
Within this environment, people have been able to create and distribute their own contents as active users and exercise control over those contents such as documents, images, and videos
(Anabel, 2012).
Once online contents are created by users, the feature of interaction can be also strengthened without the constraints of time and space. Uninhibited by the traditional boundaries of time and space, SNS users are imbued with various communicative agencies. Especially, with the ubiquity of mobile phones, accessibility to SNS has increased to an unprecedented degree
(Bernhardt et al, 2011). Interactions between people on SNSs occur every time and everywhere, and these innovative and original features of the SNSs are enough for many people to be attracted to them.
To date, many researchers applied the U&G perspective to people’s SNS use (e.g.,
Anabel, 2012; Barker, 2009; Brandtzæg & Heim, 2009; Chen, 2011; Dunne et al, 2010; Liu et
11
al., 2010; Park, 2013; Urista, 2009). For example, Urista (2009) examined the reasons why young adults use social network sites by applying the U&G framework and Barker (2009) studied older adolescents’ motivations for SNS use by drawing on the concept of group identity and collective self-esteem. One step further, Quan-Haase and Young (2010) investigated which types of motivations are better satisfied by different types of SNSs by comparing Facebook and
Instant Message.
Through intensive research employing various subjects and methods, researchers found out that individuals use SNSs to gratify diverse needs and achieve several different purposes such as social networking, passing time, identity construction, information seeking, and entertainment, among others (Anabel, 2012; Ballard, 2011; Bonds-Raacke & Raacke, 2010;
Brandtzæg & Heim, 2009; Bumgarner, 2007; Chen, 2011; Dunne et al, 2010; Java et al., 2007;
Johnson & Yang, 2009; Kwon et al., 2013; Liu et al., 2010; Park et al., 2009; Smock, 2011;
Urista et al., 2009). Even though there are different ways for users to create their profiles and
individuals use different SNSs for their specific purposes (Anabel, 2012), in aggregate, users
have basically similar motivations including entertainment, passing time, expression of their
identity, relational maintenance, information seeking, and information sharing (Anabel, 2012;
Barker, 2009; Ballard, 2011; Bonds-Raacke & Raacke, 2010; Bumgarner, 2007; Chen, 2011;
Dunne et al, 2010; Java et al., 2007; Johnson & Yang, 2009; Kwon et al., 2013; Liu et al., 2010;
Park et al., 2009; Smock, 2011; Urista et al., 2009) In addition to these primary reasons for SNS
use, there are secondary motivations as well. Users were found to search jobs and other career
information (Ballard, 2011), pursue novel trends (Bumgarner, 2007), and try to gain popularity
(Chen, 2011), all through their SNS use.
Motivation for SNS Use 12
According to the previous research, people use SNS to achieve various purposes and needs (Anabel, 2012; Dunne et al, 2010; Kwon et al., 2013). Typically, the motivations of SNS users are somewhat different, but they generally include the following purposes: Socializing, entertainment, self-status seeking, information seeking collection and connection, personal expression, initiating relationships fandom, interaction with celebrities, professional development, emotional release, information seeking, citizenship behavior, social connection, visibility (Bumgarner, 2007; Park et al., 2009; Zhang & Pentina, 2012).
Of the various motivations for SNS use, it seems that the most essential function of SNSs is to interact and communicate with others without the constraints of time and space (Brandtzæg,
& Heim, 2009). While SNSs’ key technological features are somewhat different, almost every
SNS allows users to reach beyond their pre-existing social network, and to use the truncated time
and space of the online realm to establish new friends based on their political views, similar
hobbies, shared interests, and SNS activities (Ellison, 2007). For example, Urista and others
(2009) found that a great number of people were using SNSs because they wanted to
communicate with their friends in an efficient way (Urista et al., 2009). Similarly, Dunne and his
colleagues (2010) revealed that the most important feature of SNSs for the users was chatting
and keeping in contact with their friends.
Moreover, individuals spend their time on SNSs not just for information seeking, but also
for information sharing. Unlike with information seeking, this motivation allows people to offer
some information. For example, for people who use SNSs in order to provide information that
may be useful or of interest to others, the purpose of SNS is to share information (Bumgarner,
2007). Specific motivation for sharing information is to share information that may be useful or
interesting to other users (Bumgarner, 2007). 13
Individuals do not only use SNSs for identity construction and information seeking, people also use SNS for enjoyment. There has been research showing entertainment motivation is a significant factor (Ballard, 2011; Park et al., 2009; Smoke, 2011; Kwon et al., 2013).
Individuals can do many activities on SNSs, and they derive enjoyment from the activities. The participants in Park and others’ (2009) research answered that they used Facebook to have fun by seeing other people’s pictures and to explore how others were using Facebook. Similarly, Smoke
(2011) found that people use SNSs to relax, unwind, have a pleasant rest, enjoy their day, and entertain others. Ballard (2011) also reported that people engage in SNS activities because it is enjoyable and entertaining.
With the ubiquitous online environment, people can use the Internet any time and everywhere. Thus, people can visit their SNS just for passing time. It means passing time is the one reason people use SNS without any specific purpose or needs. For example, individuals visit
SNSs when they have nothing better to do or are simply bored. Also, it is revealed that individuals spend their time using SNSs because SNSs give them something to do. Some researchers regard this motivation as just one of the routine things users do when online (Sheldon,
2008; Smoke, 2011).
Identity Construction through SNS Use
Identity construction is another critical motivation for using SNSs. It is not surprising that users care about their identity on SNSs because individuals’ profiles on SNSs are shown to others searching for them online or visiting their SNS pages. Bumganer (2007) found people are highly invested in constructing their identity on Facebook and thus expend a significant amount of time and energy on their profile. They use their Facebook profile to describe who they are.
Hence, they are more likely to think these activities as another tool of self-realization.
14
Additionally, users expect their friends to react to them by exposing personal information,
writing on walls, and expressing personal emotion (Bumgamer, 2007). Similarly, Liu and others
(2010) reported that people use SNSs to show their personality and tell others about themselves.
The self-expression motivation, in turn, was significantly associated with Facebook Intensity
(Park & Lee, 2014)
By extension, people consider how they frame their identity on SNSs in ways that make
them seem more appealing, alluring, and attractive. According to Dunne and his/her colleagues
(2010), identity creation and management was a significant reason for teens to use SNSs. They
found that teens present and manage a certain identity to achieve the goal of appearing to be
popular and cool and they choose to accomplish the goal primarily by uploading good pictures.
In a study, participants mentioned that they identified themselves by updating various personal
information on the “about me” section of their SNS profile (Dunne et al., 2010).
Additionally, people use SNSs to obtain personal information about others. Sometimes,
this information seeking is associated with other people’s personal information such as old
friends’ current lives and finding out about important events (Brandtzæg & Heim, 2009).
According to Park and others (2009), some SNS users visit the sites to actively seek out others’
personal statuses. Also, it could be related to lives shared with friends, such as events and academic affiliations (Bonds-Raacke & Raacke, 2010). On the other hand, some individuals connect to SNSs to get information about social or political issues (Chen et al., 2014). This kind
of information is often shown in the form of forwarded links, with which people usually look for
things about what is going on in society. Johnson and Yang (2009) also showed that SNS users
have motivations to get news, knowledge, and ideas, and they expect to give or receive advice
from other users.
15
Different Functions and Motivations, Different Social Networking Sites
It is also known that some SNSs are better than others in satisfying specific needs. As
people have different motivations and needs in using SNSs, they consider which SNS is more
suitable to meet their specific goals than others. For example, for people who want contact with
pre-existing friends, Facebook could be more suitable than Twitter. SNS users seeking information, on the other hand, are more likely to want to use Twitter because they can get any messages from others they follow. These different motivations make users select specific SNSs because each SNS is not only a unique relationship system, but also a dissimilar information distribution system (Ruggiero, 2000).
Closely related to the primary functions and user motivations, each SNS has different levels of privacy and publicity. In other words, the level of openness of personal information is different depending on the kind of SNS, although SNS users can adjust privacy settings and change the level of openness of their profile and personal network within the boundary set by the
SNS companies. For example, Facebook is primarily based on users’ friendship, and thus other people usually cannot access the posts or comments made by unknown users. Contrarily, Twitter users can see other people who they do not know because Twitter, by design, allows users to seek information and others’ opinions from the wide-open network (Ballard, 2011; Kwon et al.,
2013; Liu et al., 2010).
Facebook is one of the most popular SNSs in the world and a good example of closed- network SNSs. If a user requests friendship with other users and has the request accepted, then they become friends on Facebook. Thus, Facebook users’ most valuable motivation is related to bridging social capital and bonding their friendship through Facebook (Kwon et al., 2013).
According to Park and others (2009), Facebook users expect to keep in touch with their friends 16 and communicate with other people. According to the research conducted by Bumgarner (2007),
Facebook users’ first motivation for using it was social utility motivation. In this research, it is revealed that people have motivations for making friendships and maintaining connections with old and current friends. Moreover, there is a motivation to locate old friends. Park and Lee (2014) found out that University students use Facebook to maintain their relationship with friends.
Facebook is crucial for its users not only to keep in touch with existing friends, but also to establish new relationships (Park et al., 2009). When Bonds-Raacke and Raacke (2010) compared Facebook and MySpace, one of the important and distinctive purposes of using
Facebook was to make new friends. With those functions for keeping in touch with friends and establishing new connections with interesting people, people feel they are involved with other people and social communities (Kwon et al., 2013).
Even though the major and important reason why people use Facebook is for social networking or making new friends, people also seek for information through Facebook.
Especially, Facebook users search for information related to their friends, schoolwork, or events, and this could be effective in that almost all friends they keep in touch with in Facebook are their friends in reality. Thus, through Facebook, users can get information about how their old friends are, when a party will be held, and many others. According to Park et al. (2009), college student
Facebook users not only used the SNS to get news about off-campus events, but also learned about on-campus events as well. Bonds-Raacke and Raacke (2010) found out that Facebook users want to learn about social events and to achieve academic purposes.
In contrast to Facebook, Twitter is a good example of open-network SNSs. On Twitter, the notion of following and followers is prominent. This relationship of following and being followed does not require users to have reciprocation with each other. Users can follow any 17
Twitter users, and can be followed by any other people without their approval. For example, if a user follows other people, the user receives all messages that the other people they follow write on Twitter (Kwak et al., 2010).
Since Twitter is more suitable for getting information from other people’s messages (Liu et al., 2010), Twitter users have motivation to get information and give or receive advice from others such as news, knowledge, ideas, facts, and links (Johnson & Yang, 2009). It is somewhat different from Facebook users’ motive for information seeking in that information the Facebook users want to get is related just their friends’ lives.
Given that Twitter has the ability to disseminate information to many followers at a fast rate, Twitter, sometimes, allows individuals to become involved in social issues or political issues. Thus, there has been research investigating the relationship between politics and Twitter.
According to Park (2013), there are people who have the role of opinion leadership on Twitter, and opinion leaders have motivation to make an important contribution to others’ involvement in political processes. Also, Johnson and Yang (2009) indicated that people use Twitter to participate in discussions about social issues (Johnson and Yang, 2009).
Not as important as the information seeking function, Twitter can be utilized to maintain their relationship with others. Johnson and Yang (2009) indicated that Twitter users have social motivation, and this social motivation includes keeping in touch with a friend or family member, communicating more easily, and communicating with many people at the same time (Johnson &
Yang, 2009). As a crucial tool for networking and communication, Twitter can also play a crucial role for users maintaining their friendship by posting routine daily activities (Java et al.,
2007). According to Java et al. (2011), Twitter users tend to think they are connecting with their friends or family members when they spend their time or write something on Twitter because
18
they could be the followers of their friends or followed by their friends. Still, this relationship
maintenance function of Twitter is not as salient as its information seeking function.
Because of the censorship in China, Chinese SNS users cannot access US-based SNS platforms such as Facebook or Twitter. Instead, they use Chinese-based SNSs such as Weibo,
Renren, or WeChat. Among them, WeChat. is the most popular social media platform in China
(Lien & Cao, 2014). WeChat is a mobile instant text message service and acquired the popularity
with the help of rapid penetration of smartphone services. Almost everyone on a WeChat user’s
contact list is their family member or friend. According to Lien and Cao (2014), the motivations
for using WeChat include entertainment, game, emotional needs, and self-image maintenance.
On the other hand, Weibo has features like followers and following, as does Twitter. The
primary reason why Chinese people use Weibo is to get information about the society. Just as
Twitter is utilized by people to learn about news, knowledge, ideas, and facts (Johnson & Yang,
2009), Weibo users’ information need is almost always related to social issues. According to
Cheng and others (2014), cognitive needs are the most critical motivation for Weibo users. More
specifically, finding out what is going on in the society is the most important reason for Weibo
users, followed by understanding events that are happening, and broadening the knowledge base.
19
CHAPTER III. RESEARCH HYPOTHESES
The tight censorship of Internet content, including the SNSs, by the Chinese government has impact on how Chinese citizens behave on the Internet. In spite of the difficulty of conducting such studies, a few existing research illuminate how the Chinese government controls their media and public opinion (Xu et al, 2011), how the Chinese government censors user- generated online content (King et al., 2013), and how Chinese Internet users behave online (Ai,
2013). According to Ai (2013), Chinese students’ SNS use behaviors and patterns were affected by the perception of Chinese government’s surveillance. The more threat of surveillance they perceived, the more hesitant they were to upload postings related to sensitive issues. They were also more likely to avoid using Chinese SNSs.
Unfortunately, the perceived threat of surveillance appears to have detrimental impact on
Chinese youth’s political participation. According to Mou and others (2013), Internet use proficiency and time spent online are positively associated with political participation (Mou et al,
2013). The positive relationship between SNS-based political discussion and political participation was reaffirmed in another study. Xhang and Lin (2014) categorized Chinese people’s SNS use into four categories: (1) information exchange and instrumental use, (2) relational and social networking use, (3) recreational or entertainment use, and (4) SNS-based political activities (Zhang & Lin, 2014). Among the four types of SNS use, SNS-based political discussion or activities predicted Chinese people’s political participation (Zhang & Lin, 2014).
In this study, the relationships between experience with surveillance and perceived threat of surveillance held by Chinese students attending U.S. colleges and their SNS behaviors were examined in consideration of four different types of SNSs. Based on the literature review, the four difference types were created by crossing the national origin (China vs. U.S.) and network 20
openness (open vs. closed): Chinese open SNSs; Chinese closed SNSs; U.S. open SNSs; U.S.
closed SNSs. Chinese SNSs included Weibo, WeChat, Renren, and QQ, and U.S. SNSs included
Facebook, Twitter, Instagram, Pinterest, and Tumblr. Open SNSs included Weibo, Twitter,
Pinterest, and Tumblr. Closed SNSs included WeChat, Renren, QQ, Facebook, and Instagram.
Finally, Chinese open SNSs included Weibo and Chinese closed SNSs contained WeChat,
Renren, and QQ. U.S. open SNSs included Twitter, Pinterest, and Tumblr, and U.S. closed SNSs
contained Facebook and Instagram (see Figure 1).
Country of origin of the SNSs
Chinese SNS U.S. SNS
Open Openness Closed
Figure 1. A. Four Different Types of SNSs by National Origin and Network Openness.
This study had several major terms: experience with surveillance (ES), perceived threat
of surveillance (PTS), political posting (PP), social criticism (SC), privacy protection behavior
(PPB), and Private information disclosure (PID). In this research, experience with surveillance
was used to refer how many Chinese students had their experience related to surveillance and
censorship from the Chinese government. Perceived threat of surveillance denoted how Chinese
students perceived the censorship and surveillance when they were using SNSs. Politiical
posting referred to the postings Chinese students upload on their SNSs pages regarding political
events. Social criticism was one of expressive needs Chinese students were using the SNSs to 21
fulfill and indicated the desire to criticize their society, people, and other issues. Privacy
protection behavior referred to the precautions Chinese students took online to protect their
privacy. Lastly, Private information disclosure referred to the information Chinese students
disclose on their SNSs. The measurements of these concepts were discussed in the Chapter IV.
Experience with Surveillance on Different SNSs
Experience with surveillance (ES) is the extent of government surveillance one experienced when using different SNSs, whether directly or indirectly. Some Chinese students might have experienced that they could not access some specific websites when they tried to
connect to them. Even worse, they could have had their posts or comments deleted by their
government or SNS operators because their posting included some words on the “watch” list.
Indeed, some Chinese students had their Chinese SNS accounts canceled because of their posting
(Ai, 2013). Thus, Chinese students who have access to both Chinese and US SNSs may have
different experiences of surveillance depending on the national origin of the SNSs. In addition,
SNS users might have more experiences of censorship on SNSs where public can easily access
others’ information such as Weibo. Thus, it was hypothesized that experience with surveillance
would be different depending on the type of SNSs.
H1. Chinese students’ experience with surveillance will be different depending on the type of
SNSs.
H1a: Chinese students’ experience with surveillance will be higher on the Chinese SNSs
H1b: Chinese students’ experience with surveillance will be higher on the open SNSs.
H1c: Chinese students’ experience with surveillance will be the highest on the Chinese open
SNSs. 22
Perceived Threat of Surveillance on Different SNSs
Perceived threat of surveillance (PTS) is how much people are concerned about Chinese government’s surveillance when using SNSs. According to Sydell (2008), many Chinese do not even know that the Internet is being censored. For example, when some websites they want to access were blocked, they are more likely think the reason is not because of the Chinese government’s censorship, but because of just Internet connection problems or website’s technical problems. According to a poll conducted by GlobalScan on behalf of the BBC World Service, 76 percent of Chinese respondents said they felt free of online surveillance (Keck, 2014). On the other hand, others might feel not comfortable to upload certain content on SNSs because of censorship from the government. According to Ai’s research (2013), Chinese students in New
Zealand perceived that Chinese government’s monitoring was tighter on their Chinese SNSs than on Western SNSs. Thus, this study hypothesized that the perceived threat of surveillance would be different for Chinese students studying in the U.S. depending on the type of SNSs.
H2. Chinese students’ perceived threat of surveillance will be different depending on the type of
SNSs.
H2a: Chinese students’ perceived threat of surveillance will be higher on the Chinese SNSs.
H2b: Chinese students’ perceived threat of surveillance will be higher on the open SNSs.
H2c: Chinese students’ perceived threat with surveillance will be the highest on the Chinese
open SNSs.
Experience with Surveillance, Perceived Threat of Surveillance, and SNS Posting
Behaviors 23
Additionally, based on the experience with surveillance and perceived threat of surveillance, the posting behaviors such as topic selection and expression could be different.
Chinese who had experienced surveillance and/or perceived a strong threat of surveillance might monitor themselves when they post, share, or comment on their SNSs to avoid the Chinese government’s censorship. According to Ai (2013), some Chinese do not use Chinese SNSs after they experienced surveillance because they do not want to be worried their online activities. Or, people who speak freely online might do so, in spite of frequent surveillance experiences or a strong threat of surveillance. Jenkins (2013) said some Chinese uploads a number of criticisms toward their government and enjoyed the Internet without concerns about surveillance, even though they are aware of their government’s censorship programs. It means that individuals’ experience with surveillance and the level of perceived threat of surveillance would lead to specific behaviors online. Moreover, SNS users’ posting behaviors and usage might be different depending on the types of SNS. According to Ai (2012), Chinese people who have experienced western SNS are more likely to feel that western SNSs guarantee their freedom of expression and thus they can express their thoughts more freely on western SNSs. On the other hand, they did not use Chinese SNS after their posting(s) was censored and/or account was canceled. Thus, it was hypothesized that experience with surveillance and perceived threat of surveillance would make users to select some specific topics to express themselves.
H3. Experience with surveillance will be related to users’ SNS posting behaviors.
H3a. Experience with surveillance will be negatively related to users’ political posting on
SNSs.
H3b. Experience with surveillance will be negatively related to users’ social criticism on
SNSs.
24
H4. Perceived threat of surveillance will be related to users’ SNS posting behaviors.
H4a. Perceived threat of surveillance will be negatively related to users’ political posting on
SNSs.
H4b. Perceived threat of surveillance will be negatively related to users’ social
criticism on SNSs.
Predictors of Identity Construction on SNSs
In the same vein, experience with surveillance and perceived threat of surveillance would be related to identity construction such as privacy protection behavior and private information disclosure. Those with a high level of surveillance experience or perceived threat of surveillance may take more measure to protect their identity. They are also less likely to disclose their private information. Thus, it was hypothesized that experience with surveillance and perceived threat of surveillance would be related to identity construction such as private protection behavior and private information disclosure.
H5. Experience with surveillance and perceived threat of surveillance will be positively related to users’ privacy protection behavior on different SNSs.
H6. Experience with surveillance and perceived threat of surveillance will be negatively related to users’ private information disclosure on different SNSs.
Overall, this study hypothesized that experience with surveillance and perceived threat of surveillance of Chinese students in the U.S. could be different, depending on the type of SNSs.
Moreover, the relationships between experience with surveillance/ perceived threat of surveillance and SNS posting behaviors and identity strategy were investigated. c illustrates all the variables and hypotheses in this research. By investigating the relationship among the variables, this study can contribute to better understanding of Chinese students’ experiences and
25 perceived threat of surveillance, their posting behaviors and identity construction on various
SNSs.
Chinese/American
Open/ Closed
Experience Posting of Behaviors Surveillance
Perceived Identity
Threat of Construction Surveillance
Figure 2. Research Model: Experience with Surveillance, Perceived Threat of Surveillance,
Posting Behaviors, and Identity Construction.
26
CHAPTER IV. METHOD
Procedure
An online survey was conducted with Chinese students currently enrolled in universities in the Midwestern region of U.S. during five weeks, from April 7, 2016 until May 14, 2016. An e-mail invitation including a link to a Qualtrics survey was sent from the president of Chinese
Students Association (CSA) of each school, and four follow-up reminders were sent after the initial invitation. Possibly due to the completely voluntary nature of participation and, more importantly, the politically sensitive nature of the survey, the rate of response was low. Therefore, participants were recruited on the college campuses in person as well. When potential participants were first approached, they were asked whether they were from China and, if the answer was yes, they were asked for participation in the survey. Once they agreed, the survey link was sent to their email.
Once participants accessed the online survey link, they were asked to consent to participate in the study and affirm that they were 18 years or older. Moreover, they were asked to verify that they were Chinese students attending schools in the U.S. If they answered yes to this question, they started the survey; if they answered they were not a Chinese student, their survey ended right then.
At first, respondents were asked to mark all SNSs they had an account on. They were also asked to mark all SNSs they were using on a regular basis. Subsequently, these questions were posed for each SNS they were using on a regular basis: how much time they spent on the SNS per day, how often they visited the SNS, and how many followers, followings, and friends they had on the SNS, whether they experienced various forms of surveillance on the SNS, whether they perceived threat of surveillance on the SNS, which topics and expressions they usually 27
uploaded on the SNS, which privacy protection behaviors they adopted on the SNSs, and which personal information they disclosed on the SNSs. If a participant did not use any of the list SNSs on a regular basis, the person was not asked to answer these questions at all; if one used four of the listed SNSs on a regular basis, the person was asked to answer the entire set of questions four times, once for each SNSs. After the block(s) of questions was(were) presented, questions
regarding general privacy concern and socio demographic attributes were presented.
Participants
Approximately, 2000 students on the list of the Chinese Students Associations of six
universities (Bowling Green State University, Illinois State University, Michigan State
University, Toledo University, University of Michigan, and University of Iowa) in American
Midwest were invited to participate in the study through their email. A total of 191 Chinese
students participated and all respondents indicated that they were Chinese citizens studying in
the U.S. After eliminating 23 cases where there were a lot of missing or invalid responses,
answers from 168 respondents were analyzed for this study.
Measurement
Experience with Surveillance (ES)
A scale was developed in this study to measure ES. The direct/indirect nature of the
surveillance was gauged by asking whether it was self/friends or family/someone who
experienced some form of censorship. The severity of censorship was varied from “comments
censored,” “had an SNS account suspended or canceled,” to “electronically contacted”. By
combining these two dimensions, ES was measured by nine questions: (1) Have you had your
posts or comments on SNS censored before?; (2) Have your friends or family had their SNS
posts or comments censored before?; (3) Have you heard about someone’s SNS posts or 28 comments being censored before?; (4) Have you had your SNS account suspended or canceled due to your posts or comments on SNS?; (5) Have your friends or family had their SNS accounts suspended or canceled due to their posts or comments on SNS?; (6) Have you heard that someone’s SNS account was suspended or canceled due to his/her posts or comments on SNS?;
(7) Have you been contacted by SNS or the Chinese government due to your posts or comments on SNS?; (8) Have our friends or family been contacted by SNS or the Chinese government due to their posts or comments on SNS?; (9) have you heard someone was contacted by SNS or the
Chinese government due to his/her posts or comments on SNS?. The responses were captured on a 5-point Likert scale, ranging from “never (1)” to “always (5).” The reliability scores of ES on different categories of SNSs are provided below (see Table 1).
Table 1
Reliability Coefficients of Experience with Surveillance (9 items each)
SNS Type Cronbach’s Alpha
Chinese SNS .935 U.S. SNS .976 Open SNS .876 Closed SNS .958 Chinese open SNS .966 Chinese closed SNS .947 U.S. open SNS .963 U.S. closed SNS .976
Perceived Threat of Surveillance (PTS)
It was measured by six statements modified from a study of college students’ privacy perception (Lawler & Molluzzo, 2010) and another study of Chinese student’s perception of the
29
Chinese government’s censorship program (Ai, 2013). The six statements of PTS included the following: (1) My personal information is gathered by the Chinese government on SNSs; (2) My personal postings and comments are observed or filtered by the Chinese government on SNSs; (3)
Regulation and monitor of the Chinese government on SNSs bother me; (4) I know that if I upload the sensitive information on SNS these are routinely censored; (5) If I upload sensitive information on SNSs, it will be censored; (6) I can express my thoughts freely on SNSs. Sixth item in perceived threat of surveillance was reverse scored. Responses to each statement were recorded on a 5-point Likert scale ranging from “never (1)” to “always (5)”. After a factor analysis and a reliability test, the last statement, “I can express my thought freely on SNS,” was eliminated because it did not load well with the rest of items. The following are reliability scores of PTS on different types of SNSs (see Table 2).
Table 2
Reliability coefficients of Perceived Threat of Surveillance (5 items each)
SNS Type Cronbach’s Alpha
Chinese SNS .934 U.S. SNS .908 Open SNS .915 Closed SNS .928 Chinese open SNS .973 Chinese closed SNS .923 U.S. open SNS .866 U.S. closed SNS .903
30
Political Posting (PP)
This measurement was modified from a previous study (Wang et al., 2011) and political
posting was measured as part of many other topics people commonly posted on SNSs.
Participants were asked how frequently they uploaded posts on an SNS regarding these seven categories: (1) food; (2) fashion & grooming; (3) work; (4) family life; (5) romantic relationship;
(6) sports; (7) politics. Answers were obtained on a 5-point Likert scale ranging from “not at all
(1)” to “very much (5)”.
Social Criticism (SC)
Participants were asked to assess how much a specific SNS performed these eight
communicative functions: (1) to express my love for life; (2) to express my gratitude to family,
friends, others, the God; (3) to ask for support from friends, family, others; (4) to commemorate/
remember people, special days, events; (5) to complain about people, society, and things; (6) to
express deep thoughts such as ideas, goals, aspirations; (7) to entertain/ occupy myself; (8) to
wish someone a happy birthday or other special occasions. The responses were captured on a 5-
point Likert scale ranging from “not at all (1)” to “very much (5)”. The answer to the item (5)
was used in this study as a measurement of social criticism.
Privacy Protection Behavior (PPB)
The measurement of PPB was borrowed from Hoy and Milne (2013) and contained 12
statements: (1) I provide some false personal information to set up accounts on SNS; (2) I
provide false information on my profile on SNS; (3) I monitor my profiles on SNS; (4) I am
careful about the pictures of myself I post on my SNS profile; (5) I am careful about whom I friend on SNS; (6) I am careful about what groups I join on SNS; (7) I un-tag pictures on SNS;
(8)I delete messages from my wall on SNS; (9) I regularly review SNS’s personal settings; (10) I
31 control my privacy settings on SNS so that what I do on SNS do not show up on my newsfeed;
(11) I control my privacy settings on SNS so that only my friends can see my profile; (12) I use privacy controls to allow me to filter which friends’ group sees different details of my profile on
SNS. The response to each statement was recorded on a 5-point Likert scale ranging from “never
(1)” to “always (5)”. The following are reliability scores of PPB on different types of SNSs (see
Table 3).
Table 3
Reliability coefficients of Perceived Threat of Surveillance (12 items each)
SNS Type Cronbach’s Alpha
Chinese SNS .887 U.S. SNS .922 Open SNS .797 Closed SNS .908 Chinese open SNS .974 Chinese closed SNS .894 U.S. open SNS .888 U.S. closed SNS .915
Private Information Disclosure (PID)
This variable was measured by asking participants to mark all information they reveal on the profile page of each SNS they were using on a regular basis: (1) name; (2) picture; (3) age; (4) gender; (5) birthday; (6) country of origin; (7) address; (8) marital status; (9) telephone number;
(10) school attending; (11) place of employment; (12) relationship status; (13) interest; (14) hobbies; (15) favorite music; (16) favorite movies; (17) favorite books; (18) favorite TV shows;
(19) friends; (20) social activities; (21) tastes and preferences; (22) sexual preferences; (23)
32
political views; (24) religion; (25) family situation. The score for this variable was determined by
the number of categories they disclosed on their SNS profile page(s).
SNS Types
Exploratory interviews with Chinese students studying at Bowling Green State University
in Ohio, USA, identified these nine SNSs as the most commonly utilized SNSs by the student
population: Weibo, WeChat, Renren, QQ, Facebook, Twitter, Instagram, Pinterest, Tumblr.
Based on the two attributes discussed above, the SNSs were classified into one of the four
categories. Network openness was determined by each SNS’s default setting. Whereas most of
them were obvious on this attribute, Instagram was somewhat unclear because it could be used to
share content either publicly or privately. In this study, it was categorized as a closed SNS
because it is normally used for private communication, except when used for marketing purposes.
Country of origin of the SNSs
Chinese SNS U.S. SNS
Weibo Twitter, Pinterest, Tumblr Open Openness Closed WeChat, Renren, QQ Facebook, Instagram
Figure 3. Four Categories of Popular SNSs among Chinese Students in the U.S.
Demographic Variables
Six demographic characteristics were measured in this study. Among them, gender, geographical origin, experience with US SNSs prior to their study in the U.S., and education were assessed by posing closed-ended questions. The year they were born in and the duration
33
they had lived in the U.S. were asked with open-ended questions. The gender question had three responses categories, male, female, and others, and people who marked “others” were also offered a box to fill in their gender. Because all of the participants were college students, they were also asked to mark which program they were currently enrolled at their university among undergraduate, master’s, and doctoral program. The geographical origin was measured by asking where they originally came from: Mainland China, Hong Kong, Macau, Taiwan, and Others.
Because Taiwan has their own government, respondents who checked “Taiwan” were excluded at the recruitment stage. Finally, prior experience with US SNSs was measured by asking whether they used US SNSs before they came to the U.S. The answers were captured either as yes or no.
Strategies for Statistical Analysis
This study employed the SPSS statistical package for the data analysis. Following the statistical convention in media research, the statistical significance level was set at .05 or lower to determine differences between two or more means. The first hypotheses addressed the difference of experience with surveillance depending on different types of SNSs. In order to measure the first hypotheses, paired sample analysis (T-test) was conducted comparing Chinese and U.S. SNSs first, followed by open and closed SNSs. Moreover, to compare experiences with surveillance among four different types of SNSs (Chinese open SNSs, Chinese closed SNSs, U.S. open SNSs, and U.S. closed SNSs), a GLM model with repeated measures was adopted.
The second set of hypotheses were concerned with the perceived threat of surveillance on different types of SNSs. To test the hypotheses, paired sample analysis (T-test) was conducted comparing perceived threat of surveillance of Chinese and U.S. SNSs first, followed by an analysis comparing open and closed SNSs. Additionally, a repeated measures analysis (GLM) 34
was conducted in order to compare perceived threat of surveillance among four different types of
SNSs (Chinese open SNSs, Chinese closed SNSs, U.S. open SNSs, and U.S. closed SNSs).
The third group of hypotheses investigated the relationship between experience with surveillance and posting behaviors (topic selection, and expression). In order to test the third hypotheses, this study used one-way analysis of variance (one-way ANOVA) with the level of experience with surveillance as the independent variable and topic selection and expression as dependent variables.
The fourth set of hypotheses examined the relationship between perceived threat of surveillance and posting behaviors (topic selection and expression). In order to test the fourth hypotheses, one-way analysis of variance (one-way ANOVA) was conducted with the level of perceived threat of surveillance as the independent variable and topic selection and expression as dependent variables.
The fifth group of hypotheses addressed the relationship between experience with surveillance and identity construction (private protection behaviors and private information exposure). To test these hypotheses, a regression analysis was conducted.
The sixth set of hypotheses were concerned with the relationship between perceived threat of surveillance and identity construction (private protection behaviors and private information exposure). Again, a regression analysis was adopted to test the hypotheses. 35
CHAPTER V. RESULTS
Descriptive Results
This research was conducted at six Mid-Western Universities. Because the email
containing the survey link was sent to the members of Chinese Students Association from the
president of the Association at each university, potentially a total of approximately 2,000
students could have been reached. At the end of the two-week period for the data collection, 191
surveys were completed, yielding about 10% (N = 191) participation rate. After eliminating 23
cases with too many missing answers, 168 responses were retained and analyzed.
Basic Demographic Characteristics of the Participants
In total, 34.7% (n = 43) was male, and 64.5% (n = 80) was female. One respondent (0.8%) identified their gender as “other.” (n = 1) did not want to identify themselves as female or male
(see Table 4).
Table 4
Descriptive Statistics for Sex
Sex n Valid Percent
Male 43 34.7% Female 80 64.5% Others 1 0.8%
Total 124 100 Note. N = 168
The target of this study was Chinese students attending US universities. Therefore,
participants were asked to identify which program they were in. 39.0% (n = 48) of participants 36 were in an undergraduate program, 43.1% (n = 53) were in a master’s degree program, and 17.9%
(n = 22) were in a doctoral degree program (see Table 5).
Table 5
Descriptive Statistics for U.S. Degree Programs Enrolled
Status n %
Undergraduate 48 39.0% Graduate (Master’s) 53 43.1% Graduate (Doctoral) 22 17.9%
Total 123 100 Note. N = 168
The age of participants was varied from 19 to 41 years old (M = 26.60, SD = 25.00) (see
Table 6). 37
Table 6
Descriptive Statistics for Age
Age n %
19 3 2.5%
20 6 5.0%
21 12 10.1%
22 4 3.4%
23 15 12.6%
24 13 10.9%
25 14 11.8%
26 14 11.8%
27 13 10.9%
28 6 5.0%
29 4 3.4%
30 5 4.2%
31 1 0.8%
32 5 4.2%
39 2 1.7%
40 1 0.8%
41 1 0.8%
Total 119 100% Note. N = 168
38
In terms of the geographical origin, 92.7% (n = 120) reported they were from Mainland
China; 5.6% (n = 7) from Hong Kong; 1. 6% (n = 2) from Macau (see Table 7).
Table 7
Descriptive Statistics for Geographic Origin
Origin n %
Mainland China 120 92.7% Hong Kong 7 5.6% Macau 2 1.6%
Total 124 100 Note. N = 168
Regarding their prior experience with US SNSs, 45.2% (n = 56) had never used US SNSs
while in China; 54.8% (n = 68) answered they had used US SNSs before coming to the U.S.,
even though US SNSs are blocked in China by the Chinese government. 44 of participants (n =
44) did not answer this question (see Table 8).
Table 8
Descriptive Statistics for Prior Experience with US SNSs
Prior experience n %
Yes 68 54.8% No 56 45.2%
Total 124 100 Note. N = 168 39
In terms of the duration of their residency in the U.S., 21.6% (n = 25) had been living in the U.S. for 1 month to 1 year; 26.6% (n = 31) for 1 to 2 years; 20.7% (n = 24) for 2 to 3 years;
17.2% (n = 20) for 3 to 4 years; 9.7% (n = 11) for 4 to 5 years; 3.5% (n = 4) for 5 to 6 years; 1.8%
(n = 2) for 6 to 7 years. 51 of participants (n = 51) did not answer how many years they had been living in the U.S. (see Table 9).
Table 9
Descriptive Statistics for the Duration of Residency in the U.S.
Duration n %
0-1 year 25 21.6
1year-2years 31 26.6
2years-3years 24 20.7
3years-4years 20 17.2
4years-5years 11 9.7
5years-6years 4 3.5
6years-7years 2 1.8
Total 117 100 Note. N = 168
SNS Accounts
On average, participants had five (M = 5.05, SD = 2.42) different SNS accounts.
However, the number of SNS they were using on a regular basis was no more than three (M =
2.99, SD = 2.04). 40
In terms of the SNS accounts participants had, 124 (73.4%) participants had a Weibo account and 154 (91.1%) participants had a WeChat account. 82 (48.5%) of them had a Renren account and 122 (72.2%) had a QQ account. 131 (77.5%) participants had a Facebook account and 64 (37.9%) had a Twitter account. 95 (56.2%) participants had an Instagram account and 26
(15.4%) had a Pinterest account. 18 (10.7%) of them had a Tumblr account and 29 (17.2%) had another SNS account not listed on the questionnaire.
When asked which SNSs they used on a regular basis, 86 (51.2%) participants answered that they used Weibo. 139 (82.7%) participants used WeChat on a regular basis. The number of participants who answered that they used Renren regularly was 24 (14.3%) and the number for
QQ was 68 (40%). Additionally, 79 (47.0%) participants regularly used Facebook and 23 (13.7%) used Twitter. 10 (6.0%) participants used Pinterest on a regular basis and 54 (32.1%) used
Instagram. 6 (3.6%) participants used Tumblr and 11 (6.5%) answered “other”. The results revealed that Chinese students were more likely to use Chinese SNSs and closed SNSs than US
SNSs and open SNSs (see Table 10). 41
Table 10
Descriptive Statistics for SNS Accounts and Regularly used SNSs
SNSs with Accounts Regularly used SNSs
n % n %
Weibo 124 73.4% 86 51.2%
WeChat 154 91.1% 139 82.7%
Renren 82 48.5% 24 14.3%
QQ 122 72.2% 68 40%
Facebook 131 77.5% 79 47.0%
Twitter 64 37.9% 23 13.7%
Instagram 95 56.2% 10 6.0%
Pinterest 26 15.4% 54 32.1%
Tumblr 18 10.7% 6 3.6%
Others 29 17.2% 11 6.5% Note. N = 168
Descriptive Statistics for Each SNS
Among Weibo users (n = 86), they spent from 0 to 30 minutes (M = 1.08, SD = 1.49) on it on average and they visited the SNS 2-3 times a month (M = 2.74, SD = 3.06). On average, they had approximately 75 followers (M = 2.98, SD = 1.66) and 75 followings (M = 3.01, SD =
1.56). Among WeChat users (n = 124), they usually spent one and half hour (M = 4.65, SD =
1.56) and visited the WeChat for several times everyday (M = 6.85, SD = .62). They also had about 150 friends (M = 3.18, SD = 1.35) on WeChat. Regular users of Renren spent 15-45 minutes (M = 1.67, SD = 1.68) on it on a typical day and visited Renren how often??? (M = 1.88,
42
SD = 1.69). They reportedly had about 100-200 friends (M = 3.18, SD = 2.00) on Renren. In
terms of QQ users (n = 51), their time spent on QQ was approximately one hour (M = 2.47, SD =
1.97) and they visited the site once or twice a week (M = 4.73, SD = 2.12). Also, they had around
150-250 friends on QQ (M = 3.35, SD = 1.33). Facebook users spent 45–75 minutes (M = 2.60,
SD = 1.91) on it and they usually visited Facebook pages once a day (M = 5.57, SD = 1.64). On
Facebook, they had 0 to 100 friends (M = 2.94, SD = 1.413). Regular users of Twitter spent 15-
45minutes (M = 1.39, SD = 1.19) on it on average and they visited it once or two times a month
(M = 2.22, SD = 2.04). They had about 50 followers (M = 1.56, SD = 1.29) and 50 followings (M
= 1.50, SD = 1.04). Instagram users spent 30 minutes to one hour (M = 2.32, SD = 1.77) on the
SNS and they visited it two or three times a week (M = 5.06, SD = 2.18). They have 25-75 followers (M = 2.31, SD = 1.58) and 25-75 followings (M = 2.03, SD = 1.07). For Pinterest, the time spent on it was one hour to one and half hour (M = 3.00, SD = 2.44). Its users visited the
SNS once or twice a month (M = 2.33, SD = 1.96) and reported to have 100-200 followers (M =
2.67, SD = 1.06) and 1-50 followings (M = 1.20, SD = .447). For Tumblr users (n = 4), the average time spent on it was one to one and half hour (M = 2.75, SD = 2.36), and the frequency of visit was two or three times a month (M = 3.00, SD = 2.30). They had approximately 250 followers (M = 3.50, SD = 2.88) and 150 followings (M = 2.50, SD = 2.88) (see Table 11).
43
Table 11
Descriptive Statistics for the Usage Rates (Time/Visit) of Regularly Used SNSs
Time Visit
n M SD M SD Friends Followers Followings
Weibo 83 2.16 1.46 5.48 1.92 _ 2.98 3.01
WeChat 124 4.65 2.19 6.85 0.62 3.18 _ _
Renren 18 1.67 1.68 1.88 1.69 3.18 _ _
QQ 51 2.47 1.97 4.73 2.12 3.35 _ _
Facebook 65 2.60 1.91 5.57 1.64 2.94 _ _
Twitter 18 1.39 1.19 2.22 2.04 _ 1.56 1.5
Instagram 35 2.32 1.77 5.06 2.18 _ 2.31 2.03
Pinterest 6 3.00 2.44 2.33 1.96 _ 2.67 1.20
Tumblr 4 2.75 2.36 3.00 2.30 _ 3.50 3.50
Others 8 2.00 096 4.13 2.74 1.84 _ _
Note. The maximum score is 5.
Experience with Surveillance
Generally speaking, 88% of participants had experience with their government’s surveillance program (M = 1.71, SD = .77) when the ES on all regularly used SNSs was pooled together. Among all participants who used at least one SNS on a regular basis, 12.0% (n = 17) said they never had experience with surveillance on any SNS, whether Chinese or American.
Perceived Threat of Surveillance
44
Generally speaking, Chinese students rarely had perceived threat of surveillance (M =
2.29, SD = 1.10) on all of the SNSs. Among all participants, 12% (n = 17) said they had not
perceived threat of surveillance on any SNS.
Political Posting
In terms of political posting, overall, Chinese students rarely posted political issues on
their SNSs (M = 2.06, SD = .99). Even though SNS posting behaviors about political posting
depending on different types of SNS are similar, politic posting on US SNSs (M = 2.18, SD =
1.24) was only slightly higher than on Chinese SNSs (M = 2.08, SD = 1.04), and political posting was comparable between closed SNSs (M = 2.12, SD = 1.05) and open SNSs (M = 2.18, SD =
1.24). Among the four different types of SNS, political posting was the most frequently made on
US closed SNSs (M = 2.22, SD = 1.25), followed by Chinese closed SNSs (M = 2.12, SD = 1.11),
Chinese open SNSs (M = 1.95, SD = .96), and U.S. open SNSs (M = 1.62, SD = .97) (see Table
12).
45
Table 12
Means and Standard Deviations on the Measure of Politic Posting on Different Types of SNSs
Politic posting
SNS types n M SD
Overall 135 2.06 .99 Chinese SNSs 131 2.08 1.04 U.S. SNSs 99 2.18 1.24 Open SNSs 80 1.87 .89 Closed SNSs 115 2.12 1.05 Chinese open SNSs 74 1.95 .96 Chinese closed SNSs 112 2.12 1.11 U.S. open SNSs 19 1.62 .97 U.S. closed SNSs 67 2.22 1.25 Note. The maximum score is 5.
Social Criticism
Participants rarely posted social criticism on all SNSs (M = 2.26, SD = 0.96). The amount of social criticism appeared to be slightly higher on Chinese SNSs (M = 2.33, SD = 1.02)
than on US SNSs (M = 2.24, SD = 1.10). Similarly, the use of SNS for Social Criticism did not
appear to be markedly different between closed SNSs (M = 2.36, SD = .97) and open SNSs (M =
2.12, SD = 1.14). Among the four types of SNSs, the frequency of uploading social criticism
seemed to be the highest for Chinese closed SNSs (M = 2.47, SD = 1.08), followed by US closed
SNSs (M = 2.23, SD = 1.10), Chinese open SNSs (M = 2.08, SD = 1.07), and US open SNSs (M
= 1.91, SD = 1.24) (see Table 13).
46
Table 13
Means and Standard Deviations on the Measure of Social Criticism on Different Types of SNSs
Social Criticism
SNS group n M SD
Overall 134 2.26 .96 Chinese SNSs 130 2.33 1.02 U.S. SNSs 69 2.24 1.10 Open SNSs 79 2.12 1.14 Closed SNSs 115 2.36 .97 Chinese open SNSs 73 2.08 1.07 Chinese closed SNSs 112 2.47 1.08 U.S. open SNSs 19 1.91 1.24 U.S. closed SNSs 68 2.23 1.10 Note. The maximum score is 5.
Privacy Protection Behavior
The result found out that Chinese students sometimes concerned their privacy, and
protected their information online (M = 2.73, SD = 0.72). Participants’ private privacy behavior score was on Chinese SNS (M = 2.81, SD = 0.72) was higher than on U.S. SNSs (M = 2.56, SD =
0.84). The score of private privacy behaviors on closed SNSs (M = 2.77, SD =0.74) than that
score on open SNSs (M = 2.51, SD =0.70). Among four different types of SNSs, Chinese students’ privacy protection behavior on open SNSs (M = 3.64, SD = 6.21) was the highest, followed by Chinese closed SNSs (M = 2.86, SD = .77), U.S. closed SNSs (M =2.62, SD = .82), and U.S. open SNSs (M = 2.08, SD = .96) (see Table 14).
47
Table 14
Means and Standard Deviations on the Measure of Privacy Protection Behavior on Different Types of SNSs
Private privacy behaviors
SNS group n M SD
Overall 134 2.73 .72 Chinese SNSs 132 2.81 .72 U.S. SNSs 67 2.56 .84 Open SNSs 82 2.51 .70 Closed SNSs 114 2.77 .74 Chinese open SNSs 76 3.64 6.21 Chinese closed SNSs 111 2.86 .77 U.S. open SNSs 19 2.08 .96 U.S. closed SNSs 66 2.62 .82 Note. The maximum score is 5.
Private Information Disclosure
The result indicated that the private information disclosure score of Chinese students was
2.73 (M = 2.73, SD = 0.72). The mean of participants’ private information disclosure on Chinese
SNS was 5.94 (M = 5.94, SD = 5.33), and the mean of that on U.S. SNSs was 3.58 (M = 3.58, SD
= 5.37). The mean of private information disclosure on closed SNSs (M = 5.47, SD =5.54) was
5.47, and mean of that on open SNSs (M = 3.54, SD =4.90) was 2.51. Among four different types
of SNSs, the mean of Chinese students’ on open SNSs (M = 7.01, SD = 5.44) was 7.01, on
Chinese closed SNSs (M = 5.24, SD = 5.80) was 5.24, on U.S. open SNSs (M =0.60, SD = 2.14) was 0.60, and on U.S. closed SNSs (M = 3.66, SD = 5.53) was 3.66 (see Table 15).
48
Table 15
Means and Standard Deviations on the Measure of Private Information Disclosure on Different Types of SNSs
Private information disclosure
SNS group n M SD
Overall 168 6.10 5.06 Chinese SNSs 168 5.94 5.33 U.S. SNSs 166 3.58 5.37 Open SNSs 168 3.54 4.90 Closed SNSs 168 5.47 5.54 Chinese open SNSs 84 7.01 5.44 Chinese closed SNSs 168 5.24 5.80 U.S. open SNSs 122 0.60 2.14 U.S. closed SNSs 166 3.66 5.53 Note. The maximum score is 25.
Results of Hypotheses
Experience with Surveillance on Different Types of SNSs
The first set of hypotheses was designed to assess whether Chinese young people’s
experience with surveillance varies on different types of SNS. The hypothesis 1a stated that
Chinese students’ experience with surveillance would be higher on the Chinese SNS than that on
the US SNS. To test the hypothesis 1a, paired sample test (T-test) was conducted. The result of
T-test revealed that Chinese students’ experience with surveillance on Chinese SNS (M = 1.86,
SD = .80) was higher than experience with surveillance on US SNSs (M = 1.52, SD = .92), t (64)
= 5.73, p < .000 (see Table 16). Therefore, the result supported H1a.
49
Table 16
Group Differences for Experience with Surveillance between Chinese SNSs and US SNSs
SNS type n M SD t df p
Chinese SNSs 65 1.86 .80 5.73 64 .000
US SNSs 65 1.52 .92 Note. The maximum score is 5.
The hypothesis 1b stated that Chinese students’ experience with surveillance would be higher on open SNSs than on closed SNSs. In order to test hypothesis 1b, experience with surveillance on open SNSs and experience with surveillance on closed SNSs were compared by conducting paired-sample t-test. The result showed that Chinese students’ experience with surveillance on open SNSs (M = 1.76, SD = .66) was higher than experience with surveillance on closed SNSs (M = 1.48, SD = .60), t (58) = 3.69, p = .000 (see Table 17). Hence, H1b was supported.
Table 17
Group Differences for Experience with Surveillance between Open SNSs and Closed SNSs
SNS type n M SD t df p
Open SNS 59 1.76 .66 3.69 58 .000
Closed SNS 59 1.48 .60 Note. The maximum score is 5.
The hypothesis 1c presented that Chinese students’ experience with surveillance would be the highest on Chinese open SNSs among the four different types of SNSs, including Chinese
50
closed SNSs, US open SNSs, and US closed SNSs. Hypotheses 3c was tested by a GLM model
with repeated measures. The results indicated that participants’ experience with surveillance on
Chinese open SNSs (M = 2.59, SD = 3.04) was the highest among the four types of SNSs.
Chinese closed SNSs (M = 2.08, SD = .98) was the second, followed by US closed SNSs (M =
1.33, SD = .56), and US open SNS (M = 1.33, SD = .76). Mauchly’s test indicated that the
assumption of sphericity had not been assumed (p = .000), therefore, Greenhouse-Geisser
corrected tests are reported (ε = .41). However, the results show that the Chinese students’ experience with surveillance was not significantly different depending on the types of SNSs,
F(1.86) = 1.86, p = .194 (see Table 18). Therefore, the result did not support H1c.
Table 18
Group Differences for Experience with Surveillance among Four different types of SNSs
SNS Type n M SD F df p
Chinese open SNS 13 2.59 3.04 1.86 1.23 n.s.
Chinese closed SNS 13 2.08 .98
U.S open SNS 13 1.33 .76
U.S closed SNS 13 1.33 .56 Note. The maximum score is 5, n.s. = not significant
Perceived Threat of Surveillance on Different Types of SNSs
The second set of hypotheses was designed to test the differences between Chinese
students’ perceived threat of surveillance on different types of SNSs. Hypothesis 2a stated that
Chinese students’ perceived threat of surveillance would be higher on Chinese SNSs than on US
SNSs. In order to test hypothesis 2a, this study compared perceived threat of surveillance on
51
Chinese SNSs and perceived threat of surveillance on US SNSs. The results showed that perceived threat of surveillance on Chinese SNSs and US SNSs were statistically significantly different. Participants’ perceived threat of surveillance on Chinese SNSs was much higher (M =
2.37, SD = 1.02) than perceived threat of surveillance on US SNSs (M = 1.75, SD = 1.75). This difference was significant t (64) = 4.65, p = .001 (see Table 19). Hence, the results supported
H2a.
Table 19
Group Differences for Perceived Threat of Surveillance between Chinese SNSs and US SNSs
SNS type n M SE t df p
Chinese SNS 65 2.37 1.02 4.65 64 .001
U.S SNS 65 1.75 .93 Note. The maximum score is 5.
Hypothesis 2b predicted that Chinese students’ perceived threat of surveillance would be higher on open SNSs than on closed SNSs. To test hypothesis 2b, this study compared perceived threat of surveillance on open SNSs and perceived threat of surveillance on closed SNSs. The results indicated that there was a significant difference between perceptions of surveillance on open SNSs and closed SNSs, t (76) = 2.74, p = .007 (see Table 20). The result pointed out that participants’ perceived threat of surveillance on open SNSs was much higher (M = 2.43, SD =
1.18) than perceived threat of surveillance on closed SNSs (M = 2.17, SD = 1.04). Hence, the results supported H2a.
52
Table 20
Group Differences for Perceived Threat of Surveillance between Open SNSs and Closed SNSs
SNS type n M SE t df p
Open SNS 2.43 77 1.18 2.74 76 .007
Closed SNS 2.17 77 1.04 Note. The maximum score is 5.
The hypothesis 2c presented that Chinese students’ perceived threat of surveillance
would be the highest on Chinese open SNSs amongst the four different types of SNSs. This
study tested hypotheses 2c under the GLM with repeated measures. Mauchly’s test indicated that
the assumption of sphericity had been assumed (p = .128). The results showed that Chinese
students’ perceived threat of surveillance was significantly different across the four different
types of SNSs, F(1.71. 85.88) = 12.22, p = .000 (see Table 21). Therefore, the results supported
H2c.
Table 21
Group Differences for Perceived Threat of Surveillance among Four Different Types of SNSs
SNS Type n M SD F df p
Chinese open SNS 13 2.66 .97
Chinese closed SNS 13 2.08 .98 12.83 3 .000 U.S open SNS 13 1.42 .76
U.S closed SNS 13 1.60 .82 Note. The maximum score is 5.
53
Relationship between Experience with Surveillance and Posting Behaviors
The third set of hypotheses were designed to examine the relationship between Chinese students’ experience with surveillance and posting behaviors such as political posting and Social
Criticism on the different types of SNSs. To test these hypotheses, the 5-point Likert-type scale was recoded to three levels of experience with surveillance based on the distribution: low experience, medium experience, and high experience with surveillance. The H3a and H3b were partially and reversely supported in this study.
1. Chinese SNSs. Experience with surveillance on Chinese SNSs was divided into three levels: low experience, medium experience, and high experience. Among 138 participants, if their experience with surveillance score was lower than 1.80, these participants (n = 43, % = 31.2)
were categorized as having a low level of experience with surveillance. If their experience with
surveillance score was higher than 1.80 and yet equal to or lower than 2.70, these participants (n
= 42, % = 34.7) were categorized as having a medium level of experience with surveillance. If
the experience with surveillance score was higher than 2.70, these participants (n = 47, % = 34.1) were categorized as having a high level of experience with surveillance.
Political posting. A one-way between-subject ANOVA was conducted to compare the level of experience with surveillance on political posting in low experience, medium experience, and high experience groups. The three groups were different in their political posting behavior,
F(2, 126) = 16.71, p < 0.00 (see Table 22). Post hoc comparisons using the Scheffe test indicated that the mean score for low experience with surveillance group (M = 1.75, SD = 0.76) was
significantly different from either medium experience group (M = 2.42, SD = 1.09) and high
experience group (M = 3.12, SD = 1.26), respectively at the p < 0.00 level. However, medium
experience with surveillance group (M = 2.42, SD = 1.09, p = .057) did not significantly differ 54
from the high experience with surveillance group. Taken together, these results suggested that
experience with surveillance, whether medium or high, is related to political posting on Chinese
SNSs (eta = .21). Specifically, these finding suggest that when Chinese students has some
experience with surveillance are more likely to make political postings on their Chinese SNSs.
Table 22
One-Way Analysis of Variance for the Relationship between Experience with surveillance and
Political Posting on Chinese SNSs
n M SD F df p eta
Low experience 42 1.75 .76
Medium experience 41 2.42 1.09 16.78 2, 126 .000 .210
High experience 46 3.12 1.36 Note. The maximum score is 5.
Social criticism. A one-way between-subject ANOVA was conducted to compare the level of experience with surveillance on Social Criticism across low experience, medium experience, and high experience group. There was a significant effect of experience with
surveillance on Chinese SNSs, F(2,127) = 5.73, p = 0.00 (see Table 23). Post hoc comparisons
using the Scheffe test pointed out that the mean score for low surveillance experience group (M =
2.13, SD = 0.90) was significantly different from high experience group (M = 2.95, SD = 1.26) at
the p < .05. However, medium experience group (M = 2.58, SD = 2.95) did not significantly
differ from either the low experience group (M = 2.42, SD = 1.09, p = .09) or the high experience
group (M = 2.95, SD = 1.26, p = .50). Taken together, these results suggest that Social Criticism
was different depending on the level of experience with surveillance on Chinese SNSs (eta = .08). 55
In particular, those with high experience with surveillance were also more likely to express
social criticism on Chinese SNSs.
Table 23
One-Way Analysis of Variance for the Relationship between Experience with Surveillance and
Social Criticism on Chinese SNSs
n M SD F df p eta
Low experience 42 2.13 0.90 5.73
Medium experience 41 2.58 1.05 2, 127 .004 .083
High experience 46 2.95 1.26 Note. The maximum score is 5.
2. US SNSs. If a participant’s experience with surveillance score was equal to 1, they (n
= 34, % = 48.6) were categorized as having a low level of experience with surveillance. If the experience with surveillance score was higher than 1 and yet equal to or lower than 1.78, the participants (n = 19, % = 27.1) were categorized into the medium group. If the experience with surveillance score was higher than 1.78, the participants (n = 17, % = 21.4) were categorized into the high experience group.
Political posting. A one-way between-subject ANOVA was used to compare political
posting behavior of low experience, medium experience, and high experience groups on US
SNSs. There was a significant effect of experience with surveillance on political posting
behavior on US SNSs, F(2,66) = 14.29, p < 0.00 (see Table 24). Post hoc comparisons using the
Scheffe test pointed out that the mean score for low surveillance experience group (M = 1.66, SD
= 0.92) was significantly different from high experience group (M = 3.34, SD = 1.07). Medium
56
experience group (M = 2.05, SD = 1.25) was also significantly different from high experience
group (M = 3.34, SD = 1.07). However, low surveillance experience group (M = 1.66, SD = 0.92)
did not significantly differ from medium experience group (M = 2.05, SD = 1.25). Taken
together, these results suggest that the level of experience with surveillance has an effect on
political positing on US SNSs (eta = .30).
Table 24
One-Way Analysis of Variance for the Relationship between Experience with Surveillance and
Political Posting on US SNSs
n M SD F df p eta
Low experience 33 1.66 .92 14.29 2,66 .000 .30
Medium experience 19 2.05 1.25
High experience 17 3.34 1.07 Note. The maximum score is 5.
Social criticism. A one-way between-subject ANOVA was conducted to compare the level of experience with surveillance on Social Criticism across low experience, medium experience, and high experience groups on US SNSs. There was a significant difference in Social
Criticism across the three groups F(2,66) = 27.18, p < 0.00 (see Table 25). Post hoc comparisons
using the Scheffe test indicated that the mean score for low surveillance experience group (M =
1.59, SD = .775) was significantly different not only from the medium experience group (M =
2.30, SD = .83) but from the high experience group as well (M = 3.42, SD = .93). Moreover, the
medium experience group (M = 2.30, SD = .83) significantly differed from the high experience
group (M = 3.42, SD = .93). Taken together, these results show that experience with surveillance
57
was related to Social Criticism on US SNSs (eta = .45). Specifically, these results suggest that
when Chinese students’ experience with surveillance on US SNSs was high, they expressed more
Social Criticism on the online platform.
Table 25
One-Way Analysis of Variance for the Relationship between Experience with Surveillance and
Social Criticism on US SNSs
n M SD F df p eta
Low experience 33 1.59 .77 27.18 2,66 .000 .452
Medium experience 19 2.30 .83
High experience 17 3.42 .93 Note. The maximum score is 5.
3. Open SNSs. The 87 participants who answered that they were using at least one open
SNSs on a regular basis were divided into three groups depending on the level of experience with
surveillance on open SNSs. Participants with the surveillance score lower than or equal to 1.33
(n = 31, % = 38.3) were categorized as low experience with surveillance group. If score were
larger than 1.33 and smaller or equal to 2.00, these participants (n = 24, % = 29.6) were categorized as a medium experience group. If their experience score was larger than 2.00, these participants (n = 32, % = 32.1) were categorized as high experience with surveillance.
Political posting. A one-way between-subject ANOVA was conducted to compare the level experience with surveillance on political posting on Open SNSs. There was no significant effect of experience with surveillance for the three groups, F(2,68) = 2.06, p = .13 (see Table 26).
Table 26
58
One-Way Analysis of Variance for the Relationship between Experience with Surveillance and
Political Posting on Open SNSs
n M SD F df p eta
Low experience 23 1.68 .67 2.066 2,68 n.s. .057
Medium experience 23 2.19 1.05
High experience 25 1.79 .91 Note. The maximum score is 5, n.s. = not significant
Social criticism. A one-way between-subject ANOVA was used to compare the three
experience with surveillance groups on social criticism on open SNSs. There was no significant difference across the three groups in social criticism F(2,67) = 1.56, p = .21 (see Table 27).
Table 27.
One-Way Analysis of Variance for the Relationship between Experience with Surveillance and
Social Criticism on Open SNSs
n M SD F df p eta
Low experience 23 1.89 1.14 1.56 2, 67 n.s. .045
Medium experience 23 2.06 1.26
High experience 24 2.47 1.09 Note. The maximum score is 5, n.s. = not significant
4. Closed SNSs. Among 117 respondents, if the experience with surveillance score was
lower than or equal to 1.11, the participants (n = 44, % = 37.6) were categorized as a low
experience with surveillance group. Additionally, if the experience with surveillance score was
59
higher than 1.11 and lower than or equal to 1.72, the participants (n = 29, % = 29.1) were categorized as a medium experience group. If the experience with surveillance score was higher than or equal to 1.72, the participants (n = 39, % = 33.3) were categorized as a high experience with surveillance group.
Political posting. A one-way between-subject ANOVA was conducted to compare political posting behaviors of the three experience with surveillance groups on closed SNSs.
There was a significant effect of experience with surveillance on political posting behavior,
F(2,101) = 17.84, p < 0.00 (see Table 28). Post hoc comparisons using the Scheffe test indicated that the high surveillance experience group’s mean score (M = 2.87, SD = 1.07) was significantly
different from not only low group (M = 1.85, SD = .87) but also medium experience group (M =
1.67, SD = .934). Moreover, medium experience group (M = 2.30, SD = .835) significantly
differed from high experience group (M = 3.42, SD = .934). Taken together, these results
suggested that the higher a Chinese student’s experience with surveillance, the more political
postings they made on closed SNSs.
Table 28
One-Way Analysis of Variance for the Relationship between Experience with Surveillance and
Political Posting on Closed SNSs
n M SD F df p eta
Low experience 33 1.85 .87 17.84 2, 101 .000 .261
Medium experience 32 1.67 .76
High experience 39 2.87 1.07 Note. The maximum score is 5.
60
Social criticism. A one-way between-subject ANOVA was conducted to compare Social
Criticism of low experience, medium experience, and high experience groups on closed SNSs.
There was a significant effect of experience with surveillance on Social Criticism, F(2,101) =
4.991, p = 0.009 (see Table 29). Post hoc comparisons using the Scheffe test indicated that the
mean score for high surveillance experience group (M = 2.79, SD = 1.05) was significantly
different from not only the low group (M = 2.16, SD = .80) but the medium experience group as
well (M = 2.21, SD = .96). Moreover, the medium experience group (M = 2.21, SD = .96)
significantly differed from the high experience group (M = 2.79, SD = 1.05). Taken together,
these results point out that Chinese students’ experience with surveillance was related to their
Social Criticism on closed SNSs.
Table 29.
One-Way Analysis of Variance for the Relationship between Experience with surveillance and
Social Criticism on Closed SNSs
n M SD F df p eta
Low experience 34 2.16 .80
Medium experience 32 2.21 .96 4.991 2, 102 .009 .089
High experience 39 2.79 1.05 Note. The maximum score is 5.
Relationship between Perceived Threat of Surveillance and Posting Behaviors
This set of hypotheses was generated to investigate the relationship between Chinese
students’ perceived threat of surveillance and posting behaviors on the four different types of
SNSs. To test the hypotheses, the 5-point Likert-type scale was recoded to the three levels of
61 perceived threat of surveillance based on the distribution: low, medium, and high perceived threat of surveillance. The H4a and H4b were partially and reversely supported in this study.
1. Chinese SNSs. If participants’ perceived threat of surveillance score was lower than or equal to 1.80, they (n = 44, % = 34.8) were categorized into the low perceived threat group. If participants’ perception of surveillance score was higher than 1.80 and yet lower than or equal to
2.70, they (n = 43, % = 32.6) were categorized into the medium perceived threat group. If the score of perceived threat of surveillance was higher than 2.70, the participants (n =42, % = 32.6) were categorized into the high perceived threat group.
Political posting. A one-way between-subject ANOVA was used to compare political posting behavior of three perceived threat groups on Chinese SNS. There was no significant difference across the three groups, F(2,126) = 1.86, p = .16 (see Table 30).
Table 30
One-Way Analysis of Variance for the Relationship between Perceived Threat of Surveillance and Political Posting on Chinese SNSs
n M SD F df p eta
Low perception 44 1.88 0.98 1.860 2,126 n.s. .029
Medium perception 43 2.31 0.87
High perception 42 2.08 1.23 Note. The maximum score is 5, n.s. = not significant
Social criticism. A one-way between-subject ANOVA was used to compare Social
Criticism of the three groups on Chinese SNSs. There was no significant effect of perceived threat of surveillance on Social Criticism, F(2,126) = 0.36, p = .69 (see Table 31).
62
Table 31
One-Way Analysis of Variance for the Relationship between Perceived Threat of Surveillance and Social Criticism on Chinese SNSs
n M SD F df p eta
Low perception 45 2.25 .97 .368 2, 126 n.s. .006
Medium perception 43 2.43 .86
High perception 41 2.34 1.21 Note. The maximum score is 5, n.s. = not significant
2. US SNSs. There were 70 participants who were using at least one US SNS on a regular basis and they were classified into three groups based on their perceived threat of surveillance. If participants’ perceived threat score was lower than 1.6, they (n = 27, % = 38.6) were categorized as having low perceived threat of surveillance. If the perception score of participants was higher than 1.6 and lower than or equal to 2.9, they (n = 16, % = 22.8) were categorized into the medium perceived threat of surveillance group. If Chinese students’ perceived threat of surveillance score was higher than 2.9, they (n = 27, % = 38.6) were categorized into the high perceived threat of surveillance group.
Political posting. A one-way between-subject ANOVA was conducted to compare political posting behavior of the three perceived threat of surveillance groups. There was a significant effect of perceived threat of surveillance on political posting, F(2,66) = 4.39, p = .01
(see Table 32). Post hoc comparisons using the Scheffe test indicated that the mean score of the low perceived threat group (M = 1.74, SD = .95) was significantly different from the mean of the
63
high perceived threat group (M = 2.65, SD = 1.46). However, the medium perceived threat group
(M = 1.96, SD = .76) did not significantly differ from either the low group (M = 1.74, SD = .95).
Table 32
One-Way Analysis of Variance for the Relationship between Perceived Threat of Surveillance
and Political Posting on US SNSs
n M SD F df p eta
Low perception 27 1.74 .95 4.39 2,66 .016 .115
Medium perception 11 1.96 .76
High perception 31 2.65 1.46 Note. The maximum score is 5.
Social criticism. A one-way between-subject ANOVA was conducted to compare Social
Criticism of the three perceived threat groups on US SNSs. There was no significant effect of
perceived threat of surveillance on Social Criticism, F(2,66) = 2.93, p = .06 (Table 33).
Table 33
One-Way Analysis of Variance for the Relationship between Perceived Threat of Surveillance
and Social Criticism on US SNSs
n M SD F df p eta
Low perception 27 1.88 .82 2.93 2,66 n.s. .082
Medium perception 11 2.17 .88
High perception 31 2.57 1.30 Note. The maximum score is 5, n.s. = not significant
64
3. Open SNSs. If participants’ perceived threat of surveillance score was lower than or
equal to 1.60, they (n = 34, % = 34.7) were categorized as having low perceived threat of
surveillance. If the score was higher than 1.60 and lower than or equal to 2.90, the participants (n
= 31, % = 31.6) were categorized as having medium-level perceived threat of surveillance. If
Chinese students’ perceived threat of surveillance score was higher than 2.90, they (n = 33, % =
33.7) were categorized as high perceived threat of surveillance.
Political posting. A one-way between-subject ANOVA was conducted to compare political posting behavior of the three perceived threat groups on open SNSs. There was no significant effect of perceived threat of surveillance on political posting, F(2,76) = .95, p = .49
(see Table 34).
Table 34
One-Way Analysis of Variance for the Relationship between Perceived Threat of Surveillance and Political Posting on Open SNSs
n M SD F df p eta
Low perception 27 1.93 .85 .905 2, 76 n.s. .23
Medium perception 28 2.01 .89
High perception 24 1.68 .95 Note. The maximum score is 5, n.s. = not significant
Social criticism. A one-way between-subject ANOVA was used to compare Social
Criticism of the three perceived threat of surveillance groups. There was no significant effect of
perceived threat of surveillance on Social Criticism, F(2,66) = 2.75, p = .78 (see Table 35).
65
Table 35
One-Way Analysis of Variance for the Relationship between Perceived Threat of Surveillance
and Social Criticism on Open SNSs
n M SD F df p eta
Low perception 27 2.00 1.03 .246 2, 75 n.s. .007
Medium perception 28 2.21 1.15
High perception 23 2.15 1.29 Note. The maximum score is 5, n.s. = not significant
4. Closed SNSs. If participants’ perceived threat of surveillance score was lower than or
equal to 1.50, they (n = 41, % = 33.6) were categorized as having low perceived threat of
surveillance. If the score was higher than 1.50 and lower than or equal to 2.53, the participants (n
= 40, % = 32.8) were categorized as having medium-level perceived threat of surveillance. If
Chinese students’ perceived threat of surveillance score was higher than 2.53, they (n = 41, % =
33.6) were categorized as high perceived threat of surveillance.
Political posting. A one-way between-subject ANOVA was conducted to compare political posting behavior of the three perceived threat of surveillance groups on closed SNSs.
There was no significant effect of perceived threat of surveillance on political posting on closed
SNSs, F(2,109) =1,94, p = .148 (Table 36).
66
Table 36
One-Way Analysis of Variance for the Relationship between Perceived Threat of Surveillance and Political Posting on Closed SNSs
n M SD F df p eta
Low perception 40 1.87 .844 1.946 2, 109 n.s. .034
Medium perception 35 2.31 .931
High perception 37 2.23 1.31 Note. The maximum score is 5, n.s. = not significant
Social criticism. A one-way between-subject ANOVA was used to compare Social
Criticism of three different perceived threat of surveillance groups on closed SNSs. There was no
significant effect of perceived threat of surveillance on Social Criticism, F(2,110) = 1.58, p
= .211 (see Table 37).
Table 37
One-Way Analysis of Variance for the Relationship between Perceived Threat of Surveillance and Social Criticism on Closed SNSs
n M SD F df p eta
Low perception 40 2.16 .70 1.580 2,110 n.s. .028
Medium perception 36 2.40 .94
High perception 37 2.55 1.19 Note. The maximum score is 5, n.s. = not significant
Predictors of Privacy Protection Behaviors
67
The fifth set of hypotheses was designed to examine the relationship between Chinese
students’ surveillance variables such as experience with surveillance and perceived threat of
surveillance and privacy protection behaviors on the different types of SNSs. To test these
hypotheses, hierarchical regression analysis was conducted. The H5 was partially and reversely
supported in this study.
1. Chinese SNSs. A hierarchical multiple regression was conducted in order to which
variable predicts privacy protection behavior. Demographic variables (gender, age, status) were
included in the first block as control, but it was not significant, R2 change = .030, F(3,106) =
1.104, p = .315. Introducing the exposure to U.S variables (duration, prior experience) explained
its significance, R2 change = .072, F(2,104) = 4.172, p = .018. The addition of the third block
including experience with surveillance and perceived threat of surveillance resulted with
2 significant change, R change = .117, F(2,102) = 7.635, p = .001 (see Table 38).
Table 38
Summary of Hierarchical Regression Analysis for Variables Predicting PPB on Chinese SNSs
Model 1 Model 2 Model 3
Variable B SE B β B SE B β B SE B β
Gender -.063 .157 -.040 .019 .157 .012 .120 .152 .076 Age .000 .000 .105 .000 .000 .054 .000 .000 .028 Status -.115 .101 -.113 -.128 .101 -.126 -.076 .097 -.075 USSNS -.199 .143 -.132 -.136 .138 -.090 Duration .010 .004 .241* .009 .004 .221* ES .328 .096 .348 PTS .016 .064 .025** R2 0.030 0.102 0.219
F for change in R2 1.104 4.172* 7.635**
* p < .05. ** p < .01. *** p < .001
68
2. US SNSs. A hierarchical multiple regression was calculated to predict privacy
protection behaviors based on demographic variables (gender, age, status), exposure to U.S.
variables (duration, prior experience), and surveillance variables (experience with surveillance,
perceived threat of surveillance). Demographic variables (gender, age, status) were included in
the first block as control, but it was not significant, R2 change = .050, F(3,54) = .941, p = .427.
Adding exposure to U.S. variables did not explain its significance, R2 change =.051, F(2,52) =
1.485, p = .236. Finally, the addition of surveillance variables (experience with surveillance,
perceived threat of surveillance) to the regression model, R2 change = .349, F(2,50) = .349, p
= .000, was significant (see Table 39).
Table 39
Summary of Hierarchical Regression Analysis for Variables Predicting PPB on US SNSs
Model 1 Model 2 Model 3
Variable B SE B β B SE B β B SE B β
Gender .393 .275 .211 .466 .278 .250 .730 .227 .392** Age .000 .001 -.037 .000 .001 -.090 .000 .000 -.118 Status -.235 .177 -.198 -.295 .181 -.248 -.060 .150 -.051 USSNS .016 .245 .009 -.078 .203 -.044 Duration .011 .006 .234 .006 .005 .132 ES .508 .169 .529** PTS .146 .160 .158 R2 .050 .101 .451
F for change in R2 .941 1.485 15.901***
* p < .05. ** p < .01. *** p < .001
69
3. Open SNSs. A hierarchical multiple regression was conducted to predict privacy
protection behaviors based on demographic variables (gender, age, status), exposure to U.S.
variables (duration, prior experience to U.S SNS), and surveillance variables (experience with
surveillance, perceived threat of surveillance). In the first block, gender, age, and status variables
were included, but it did not explain significant, R2 change = 1.346, F(3,63) = 70, p = .268.
Introducing the duration and prior experience U.S SNS variables did not explain its significance,
R2 change =.01, F(2,61) = 3.686, p = .031.The addition of the third block including experience
with surveillance and perceived threat of surveillance resulted with significant change, R2 change
= .115, F(2,59) = 4.680, p = .013 (see Table 40).
Table 40
Summary of Hierarchical Regression Analysis for Variables Predicting PPB on Open SNSs
Model 1 Model 2 Model 3
Variable B SE B β B SE B β B SE B β
Gender .304 .208 .183 .417 .206 .250* .602 .204 .361** Age .000 .000 .122 .000 .000 .034 -9.403 .000 -.030 Status .085 .126 .084 .064 .127 .064 .101 .121 .100 USSNS -.220 .179 -.151 -.288 .173 -.197 Duration .012 .005 .291* .013 .005 .307* ES .111 .078 .190 PTS .278 .160 .230 R2 .060 .162 .162
F for change in R2 1.346 3.686* 4.680**
* p < .05. ** p < .01. *** p < .001
70
4. Closed SNSs. A hierarchical multiple regression was calculated to predict privacy
protection behaviors based on demographic variables (gender, age, status), exposure to U.S.
variables (duration, prior experience to U.S SNS), and surveillance variables (experience with
surveillance, perceived threat of surveillance). Gender, Age status variables were included in the
first block, and it was not significant, R2 change = -.027, F(3,95) = .887, p =.451. Introducing the
exposure to U.S. variables (duration, prior experience to U.S SNS) explained its significance, R2
change =.077, F(2,93) = 4.00, p = .021. Finally, the addition of surveillance variables to the
regression model, R2 change = .150, F(2,91) = 9.17, p = .000, were significant (see Table 41).
Table 41
Summary of Hierarchical Regression Analysis for Variables Predicting PPB on Closed SNSs
Model 1 Model 2 Model 3
Variable B SE B β B SE B β B SE B β
Gender .085 .167 .053 .174 .166 .110 .314 .158 .198* Age .000 .000 .028 .000 .000 -.026 .000 .000 -.052 Status -.162 .108 -.159 -.200 .108 -.196 -.131 .102 -.128 USSNS -.076 .153 -.050 -.038 .148 -.025 Duration .011 .004 .282** .009 .004 .234* ES .319 .110 .347** PTS .072 .086 .099 R2 .165 .323 .505
F for change in R2 .887 4.006* 9.177***
* p < .05. ** p < .01. *** p < .001
71
Predictors of Private Information Disclosure
The sixth set of hypotheses was designed to examine the relationship between Chinese
students’ surveillance variables such as experience with surveillance and perceived threat of
surveillance and private information disclosure on the different types of SNSs. To test these
hypotheses, hierarchical regression analysis was used. The H6 was partially supported in this
study.
1. Chinese SNSs. A hierarchical multiple regression was calculated in order to which
variable predicts private information disclosure. Demographic variables (gender, age, status)
were included in the first block as control, but it was not significant, R2 change = .03, F(3,105) =
1.13, p = .34. Introducing the exposure to U.S variables (duration, prior experience) explained with no significance, R2 change = .053, F(5,103) =1.90, p = .10. The addition of the third block
including experience with surveillance and perceived threat of surveillance resulted with
2 significant change, R change = .066, F(7,101) = 2.56 p = .01 (see Table 42).
72
Table 42
Summary of Hierarchical Regression Analysis for Variables Predicting PID on Chinese SNSs
Model 1 Model 2 Model 3
Variable B SE B β B SE B β B SE B β
Gender -.086 1.020 -.008 .224 1.031 .022 .778 1.031 .076 Age .003 .003 .097 .002 .003 .057 .001 .003 .036 Status -.864 .657 -.132 -.810 .665 -.123 -.542 .656 -.083 USSNS -1.680 .943 -.172 -1.436 .931 -.147 Duration .041 .026 .158 .037 .025 .140 ES 1.541 .660 .253* PTS .153 .433 .038 R2 .031 .084 .151
F for change in R2 .119 1.287 .464*
* p < .05. ** p < .01. *** p < .001
2. US SNSs. A hierarchical multiple regression was calculated in order to which variables
predict private information disclosure. Demographic variables (gender, age, status) were
included in the first block as control, and it did not predict private information disclosure, R2
change = .04, F(3,55) = .83, p = .48. Adding the exposure to U.S variables (duration, prior
experience) explained with no significance, R2 change = .07, F(5,53) =1.375, p = .24. The
addition of the third block including experience with surveillance and perceived threat of
surveillance resulted with no significant change, R2 change = .01, F(7,51) = 1.05 p = .40 (see
Table 43).
73
Table 43
Summary of Hierarchical Regression Analysis for Variables Predicting PID on US SNSs
Model 1 Model 2 Model 3
Variable B SE B β B SE B β B SE B β
Gender -1.76 1.62 -.16 -2.30 1.61 -.20 -2.59 1.67 -.23 Age 6.39 .00 .00 .00 .00 .07 .00 .003 .07 Status -.61 1.02 -.08 -.69 1.03 -.10 -.94 1.08 -.13 USSNS 2.58 1.41 .24 2.62 1.45 .25 Duration -.04 .038 -.14 -.03 .039 -.12 ES -.72 1.16 -.12 PTS .04 1.04 .00 R2 .04 .11 .12
F for change in R2 .83 2.13 .35
* p < .05. ** p < .01. *** p < .001
3. Open SNSs. A hierarchical multiple regression was calculated in order to which
variables predict private information disclosure. Demographic variables (gender, age, status)
were included in the first block as control, but it was not significant, R2 change = .04, F(3,64)
= .88, p = .45. Introducing the exposure to U.S variables (duration, prior experience) did not
explain significance, R2 change = .78, F(5,62) =.84, p = .52. The addition of the third block
including experience with surveillance and perceived threat of surveillance resulted with no
significant change, R2 change = .04, F(7,60) = .59, p = .75 (see Table 44).
74
Table 44
Summary of Hierarchical Regression Analysis for Variables Predicting PID on Open SNSs
Model 1 Model 2 Model 3
Variable B SE B β B SE B β B SE B β
Gender 1.62 1.35 .150 1.34 1.41 .12 1.32 1.49 .12 Age .00 .00 .104 .002 .00 .11 .00 .00 .11 Status .23 .80 .037 .536 .84 .08 .49 .87 .07 USSNS -1.31 1.20 -.13 -1.35 1.25 -.14 Duration -.024 .03 -.08 -.02 .036 -.09 ES .13 .55 .03 PTS -.30 1.14 -.03 R2 .04 .06 .06
F for change in R2 .886 .784 .045
* p < .05. ** p < .01. *** p < .001
4. Closed SNSs. A hierarchical multiple regression was calculated to private information
disclosure based on experience with surveillance and perceived threat of surveillance. Gender,
age, and status variables were included in the first block as control, but it was not significant, R2
change = .086, F(3,95) = 86, p = .96. Adding the duration variables did not explain its
significance, R2 change =., F(5,93) = .579, p = .71. Finally, the addition of experience with
surveillance and perceived threat of surveillance variables to the regression model, R2 change
= .013, F(7,91) = .58, p = .76, was not significant (see Table 45).
75
Table 45
Summary of Hierarchical Regression Analysis for Variables Predicting PID on Closed SNSs
Model 1 Model 2 Model 3
Variable B SE B β B SE B β B SE B β
Gender .13 1.13 .01 -.26 1.16 -.025 -.05 1.19 -.00 Age .00 .00 -.01 .00 .00 .00 5.24 .00 .00 Status -.37 .73 -.05 -.06 .75 -.01 .08 .77 .013 USSNS 10.42 6.15 -1.19 1.07 -.11 -.99 1.12 -.097 Duration -.035 .029 -.12 -.03 .02 -.14 ES .83 .83 .13 PTS -.14 .65 -.02 R2 .052 .174 .207
F for change in R2 .08 1.31 .61
* p < .05. ** p < .01. *** p < .001
76
CHAPTER VI. DISCUSSION
In this study, the types of SNSs were based on their national origin and network openness.
Based on the understanding of SNSs regularly used by Chinese students studying at US universities, this study investigated the differences in experiences with surveillance and perceived threat of surveillance across the four different types of SNSs. This study also examined the relationship between the surveillance variables (experience and perceived threat) and their SNS posting behaviors and identity construction on SNSs.
First, the findings of this study indicated that Chinese students’ experience with surveillance varied depending on different types of SNSs. Comparing Chinese SNSs and US
SNSs, experience with surveillance was found to be higher on Chinese SNSs than on US SNS.
Additionally, Chinese students’ experience with surveillance on open SNSs was higher than their experience on closed SNSs. When the two factors of national origin and network openness were combined, the mean of experience with surveillance score was the highest on Chinese open
SNSs, followed by Chinese closed SNSs, US closed SNSs, and US open SNSs. Although this order was in line with the hypothesized highest mean of experience with surveillance on Chinese open SNSs, the differences across four types of SNSs were not statistically significant. This could have been because of the small sample size since only thirteen participants used all four different types of SNSs among all of the participants. The sample size for comparing the four different types of SNSs could have been simply too small to generate a statistically significant result.
It was particularly interesting that Chinese students had experience with surveillance not only on Chinese SNSs, but also on US SNSs, although the level of surveillance experience was significantly lower on US SNSs. Due to a lack of independently verifiable source regarding the 77
reach of Chinese government’s censorship programs, we cannot verify whether the Chinese
government really censors US SNSs. However, at least some of the study participants reported
that they experienced censorship by the Chinese government on the non-Chinese SNSs.
Second, the results of this study pointed out that Chinese students had different levels of
perceived threat of surveillance, depending on the national origin and openness of SNSs. They
had much higher perceived threat of surveillance on Chinese SNSs than on US SNSs. Also, their
perceived threat of surveillance was higher on open SNSs than on closed SNSs. Among the four
different types of SNSs, Chinese students had the highest perceived threat of surveillance on
Chinese open SNSs, followed by Chinese closed SNSs, US closed SNSs, and US open SNSs.
This time, the difference across the four groups was statistically significant. Even though the
Chinese young adults’ perceived threat of surveillance on US SNSs were relatively low, they
were still concerned about being monitored by their government on the SNSs that were supposed
to be out of their government’s direct control.
Furthermore, this study found a relationship between experience with surveillance and
political posting. With the exception of open SNSs, Chinese students’ experience with surveillance was associated with political posting. Similarly, Chinese students’ experience with surveillance was associated with social criticism on Chinese SNS, US SNSs, and closed SNSs.
First and foremost, these findings support the notion that experience with surveillance is related to how people use SNSs for their social and political expression. At the same time, it should be noted that the nature of the relationship was the opposite of what was predicted. In other words, the more experience with surveillance Chinese students had, the more political postings they made. On a hindsight, though, this opposite finding makes sense because people who upload more political postings are more likely to experience surveillance as well. Because the current 78 study is based on survey data and thus a time sequence between political posting behavior and experience with surveillance cannot be established.
Regarding the lack of such relationship on open SNSs, one might speculate that the openness made people vulnerable regardless of their experience with surveillance and thus eliminated any potential influence of surveillance experience. Alternatively, it is also possible that surveillance experience is irrelevant on open SNSs because people do not need to disclose their real identities such as real name or real picture on open SNSs. Thus, they might think they can avoid the Chinese government’s censorship since they could construct other identities on open SNSs even though they have higher experience with surveillance.
When the relationships between perceived threat of surveillance and political posting as well as social criticism were examined, significance relationships were found only on US SNSs.
In other words, perceived threat of surveillance was not related to SNS posting behaviors on
Chinese SNSs, open SNSs, and closed SNSs. Also, the significant relationship between perceived threat of surveillance and political posting was in the opposite direction: People with higher perceived threat of surveillance on US SNSs uploaded more political postings.
Lastly, the relationship between the surveillance variables and identity strategies on SNSs were examined. When the criterion variable was privacy protection behavior, experience with surveillance is the primary predictor. Furthermore, the regression model indicated that the duration Chinese students lived in the U.S. was another important predictor of their privacy protection behavior. The longer they lived in the U.S., the more measures they were likely to take to protect their privacy. While living in China, they might not have been aware that they were being censored by the Chinese government and they became more sensitive to the issue only after living in the U.S. for a while. 79
Additionally, the results indicated that Chinese students’ experience with surveillance was a positive predictor of private information disclosure only on Chinese SNSs. Similar to the relationship between surveillance experience and SNS posting behaviors, people who disclosed more personal information on Chinese SNSs were more likely to have experienced their government’s surveillance. There was no relationship between surveillance variables and private information disclosure on US SNSs, open SNSs, and closed SNSs.
Additionally, the results indicated that Chinese students’ experience with surveillance was a positive predictor of private information disclosure only on Chinese SNSs. Similar to the relationship between surveillance experience and SNS posting behaviors, people who disclosed more personal information on Chinese SNSs were more likely to have experienced their government’s surveillance.
Compared to previous qualitative study, this study used quantitative method. According to the study of Ai (2013), for example, she conducted an interview to get to know how Chinese students’ perception of surveillance, and their experience with surveillance. And how those affected on their SNS usage. This study tried to statistically verify and indicated the relationship between Chinese students’ surveillance experience and perception and their behaviors such as postings and identity construction. To further, this study examined how these relationships would be different depending on different types of SNSs.
Limitations
There are a few limitations of this study. First, the sample size is small. Although this study had 169 participants in total who used at least one SNS, there were only 13 participants who used all four SNSs. Specifically, in order to compare the four different types of SNS, this study needs to have more respondents on each type of SNSs. For example, Chinese students 80
were more likely to use Chinese SNSs, and less likely to use US open SNSs. Therefore, it was
difficult to find respondents who used all four types of SNSs. If the sample size was larger, more
statistical tests could have been conducted and more significant differences could have been
discovered.
Second, in order to accurately compare the different types of SNSs, the questions for each
SNS were kept consistent. However, each SNS has different functions based on their primary purpose. Hence some questions were not exactly relevant to all SNSs. For example, WeChat users were asked which information they revealed on WeChat among 25 items, although WeChat does not have all 25 items as its basic setting. Thus, it might have confused some participants while they were taking the survey.
Third, Chinese students may experience and consider not only online censorship by their government, but offline censorship as well. Even though statements in the questionnaire asked them to think about online surveillance, they might not have been able to distinguish online and offline surveillance. It would provide more conceptual clarity if the two types of government surveillance are differentiated and controlled in future studies. 81
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APPENDIX A. HSRB APPROVAL 90
APPENDIX B. INVITATION EMAIL TO PRESIDENT OF CHINESE STUDENTS ASSOCIATION
Dear Chinese Students Association officers,
Hello, this is Kisun.
I am a master’s student in the School of Media and Communication at Bowling Green State University, Ohio. I am writing my master’s thesis about identity construction of Chinese college students in the U.S. Thus I need to conduct a survey of Chinese students attending a college in the U.S. and help of Chinese students on your campus will be crucial for timely completion of my master’s thesis.
The information Chinese students give me will be kept confidential, and no individual will be identified in the research report. Also, there are no risks involved in participating in this study beyond those encountered in normal daily life.
Could you send emails including a link to Qualtrics survey to Chinese students on your member list?
If you have any questions about the survey or if you would like more information regarding this study, please feel free to contact me to the email or phone number provided below.
I appreciate your help.
Sincerely,
Kisun Kim
302 West Hall
School of Media and Communication
Bowling Green State University
Bowling Green, OH, 43403
419-819-9866 [email protected] 91
APPENDIX C. INVIATION EMAIL TO STUDENTS
Dear CSA Students,
Hello, I invite you to participate in a study that will help gain valuable insights into SNS behaviors of Chinese students attending college in the U.S.
I am a master’ student in the School of Media and Communication at Bowling Green State University, Ohio. I am writing my master’s thesis about identity construction of Chinese college students in the U.S. Thus I need to conduct a survey of Chinese students attending a college in the U.S., and your help will be crucial for timely completion of my master’s thesis.
The information Chinese students give me will be kept confidential, and no individual will be identified in the research report. Also, there are no risks involved in participating in this study beyond those encountered in normal daily life.
The survey link is below: https://bgsu.az1.qualtrics.com/SE/?SID=SV_d6xMzUutK73I4uN
If you have any questions about the survey or if you would like more information regarding this study, please feel free to contact me to the email or phone number provided below.
I appreciate your help.
Sincerely, Kisun Kim
302 West Hall School of Media and Communication Bowling Green State University Bowling Green, OH, 43403 419-819- 9866 [email protected] 92
APPENDIX D. INFORMED CONSENT
You are invited to participate in an academic research. This study is conducted by Kisun Kim, a master student, and Dr. Sung-Yeon Park, an advisor, in the School of Media and Communication at Bowling Green State University located in Ohio, USA. To participate in this study, you must be 18 years or older.
Purpose: The goal of the current study is to learn how Chinese students’ perceived threat of surveillance and prior experiences with surveillance are different depending on diverse types of Social Network Services (SNS). Furthermore, the purpose of the present study is to investigate how both of perceived threat of surveillance and prior experience with surveillance are associated with their identity construction on SNSs. The findings from the study will help us understand Chinese students’ perception toward Chinese government regulation on SNSs, and identify ways to improve the function of the SNSs fitting into users’ preferences and the Internet policy. Although you will not receive a monetary reward, you will indirectly benefit from the knowledge gained from this study. The findings will be made widely available to academic researchers, the politician community, SNS companies, and others interested in the issues explored here.
Procedures: You will be asked to participate in an electronic survey. The completion of the survey should take no longer than 40 minutes. Upon giving consent below by selecting “Yes”, you will be taken directly to the survey.
Voluntary Nature: Your participation is completely voluntary. You may decide to skip questions or discontinue participation at any time without penalty. Deciding to participate or not will not affect your relationship with any individual or institution involved in or participating in this study.
Confidentiality: Data will be protected in locked files in a password protected computer. Only primary investigators, Kisun Kim and Dr. Sung-Yeon Park, will have access to the originally collected data. In the data collection process, your name and survey answers are collected into 93 separate databases and your name will be stored in aggregate with all other participants’ names. In the report, your identity will never be linked to your answers.
Risks: There are no risks anticipated greater than those encountered in day-to-day life. Once again, if you find related to surveillance on SNS to be a sensitive topic or feel uncomfortable answering the questions, you are free to withdraw from the study and you may do so with no penalty.
Contact Information: Please feel free to contact Kisun Kim ([email protected] | 1 (US code)- 419-819-9866) and Dr. Sung-Yeon Park ([email protected] | 1 (US code)-419-372-4322) if you would like more information regarding this study. You may also contact the Human Subjects Review Board of Bowling Green State University ( [email protected] | 1 (US code)-419-372-7716) if you have any questions about your rights as a participant in this research. If you agree to be in this study, you may continue with the survey below. Thank you very much for considering to participate in this study.
I, (Name)______, have been informed of the purposes, procedures, risks and benefits of this study. I had the opportunity to have all my questions answered and I have been informed that my participation is completely voluntary. I agree to participate in this research. I understand that I am giving consent to take part in the study by clicking “yes” below. Please click “yes,” if you give consent to participate in this study. By clicking yes, you will be taken directly to the survey. Click “no,” if you would like to opt-out of the study. 94
APPENDIX E. QUESTIONNAIRE
Dear Chinese Students,
You are invited to participate in an academic research. This study is conducted by Kisun Kim, a master student, and Dr. Sung-Yeon Park, an advisor, in the School of Media and Communication at Bowling Green State University located in Ohio, USA. To participate in this study, you must be 18 years or older. The goal of the current study is to learn how Chinese people in U.S. are using various social media. The findings from the study will help us understand how people in U.S. use various social media and identify the function of the SNSs to better serve their users. You will be asked to participate in an online survey. The completion of the survey should take less than 30 minutes. Upon giving consent below by selecting “Yes”, you will be taken directly to the survey. Your participation is completely voluntary. You may decide to skip questions or discontinue participation at any time without penalty. Deciding to participate or not will not affect your relationship with any individual or institution involved in or participating in this study. Should you decide to participate in this study, you are eligible to a random drawing for two 25$ Amazon gift cards among all participants of this study. To enter the random drawing for the prize, simply complete the questionnaire and provide your email address at the end of the survey. Data will be protected in locked files in a password protected computer. Only primary investigators, Kisun Kim and Dr. Sung-Yeon Park, will have access to the originally collected data. Your answers will be stored in aggregate data. In the report, you will never be identify as study participant. If you provide your e-maill address for random drawing, it will be used for that process only. It will be separated from your answers and discarded once the study is completed.
There are no risks anticipated greater than those encountered in day-to-day life. Once again, if you feel uncomfortable answering the questions, you are free to withdraw from the study and you may do so with no penalty.
Please feel free to contact Kisun Kim ([email protected] | 419-819-9866) and Dr. Sung- Yeon Park ([email protected] | 419-372-4322) if you would like more information regarding this study. You may also contact the Human Subjects Review Board of Bowling Green State University ( [email protected] | 419-372-7716) if you have any questions about your rights as a participant in this research. If you agree to be in this study, you may continue with the survey below. Thank you very much for considering to participate in this study.
I have been informed of the purposes, procedures, risks and benefits of this study. I had the opportunity to have all my questions answered and I have been informed that my participation is completely voluntary. I agree to participate in this research. I understand that I am giving consent to take part in the study by clicking “yes” below. Please click “yes,” if you give consent to participate in this study. Click “no,” if you would like to opt-out of the study. 95
Yes
No
Please Check all social networking sites (SNSs) that you have an account on. ( ) Weibo ( ) Wechat ( ) RenRen ( ) FaceBook ( ) Twitter ( ) Pinterest ( ) Instagram ( ) Tumblr ( ) Others
Please Check all social networking sites (SNSs) that you usually use. ( ) Weibo ( ) Wechat ( ) RenRen ( ) FaceBook ( ) Twitter ( ) Pinterest ( ) Instagram ( ) Tumblr ( ) Others
* Same set of questionnaire was asked to participant based on the second questions.
How much time do you spend on Weibo on a typical day?
0 – 30min 30min-1hr 1hr-one and One and 2hrs-one two and half More than half hour half hour – and half hour – 2hrs 3hrs 2hrs hour
How often do you visit Weibo? 96
Less than Once a Once 1 to 3 Once every Once 2-3 Once every Several once a month weeks week times a day times every month week day
How many followers do you have on Weibo?
( ) 1 -50 ( ) 50 to 100 ( ) 100 to 200 ( ) 200 to 300 ( ) 300 to 500 ( ) Over 500
Please check the number that best reflects your thoughts about Weibo.
Never Rarely Someti Often Always mes My personal information on Weibo is gathered by 1 2 3 4 5 the Chinese government. My personal postings and comments on Weibo 1 2 3 4 5 are observed or filtered by the Chinese government. Chinese government’s regulations and 1 2 3 4 5 monitoring of Weibo posts and comments bother me. If I upload sensitive information on Weibo, it will 1 2 3 4 5 be censored. I am afraid of surveillance on Weibo, even 1 2 3 4 5 though I have nothing to hide. I can express my thoughts freely on Weibo. 1 2 3 4 5
Please check the number that best reflects your experiences, direct or indirect, with censorship on Weibo. 97
Never Rarely Someti Often Always mes Have you had your posts or comments on Weibo 1 2 3 4 5 censored before? Have your friends or family had their Weibo 1 2 3 4 5 posts or comments censored before? Have you heard about someone’s Weibo posts or 1 2 3 4 5 comments being censored before? Have you had your Weibo account suspended or 1 2 3 4 5 canceled due to your posts or comments on the SNS? Have your friends or family had their Weibo 1 2 3 4 5 accounts suspended or canceled due to their posts or comments on the SNS? Have you heard that someone’s Weibo account 1 2 3 4 5 was suspended or canceled due to his/her posts or comments on the SNS? Have you been contacted by Weibo or the 1 2 3 4 5 Chinese government due to your posts or comments on the SNS? Have your friends or family been contacted by 1 2 3 4 5 Weibo or the Chinese government due to their posts or comments on the SNS? Have you heard that someone was contacted by 1 2 3 4 5 Weibo or the Chinese government due to his/her posts or comments on the SNS?
How much do you talk about these topics on Weibo? Please check the number that best reflects your Weibo posting activities, including posts, sharing, and comments you usually upload on Weibo.
Never Rarely Someti Often Always mes Food (e.g., restaurants, cooking, food, beverages, 1 2 3 4 5 pastries) Fashion & Grooming (e.g., brands, products, 1 2 3 4 5 trends, clothing, bags, cosmetics, accessories) Work (e.g., workplace, tasks, re/assignments, 1 2 3 4 5 promotion, projects) Family life (e.g., kids, vacations, trips, family 1 2 3 4 5 visits, happenings with extended family members) Romantic relationship (e.g., dating, 1 2 3 4 5 girlfriend/boyfriend, have a crush on someone) 98
Sports (e.g., games, teams, athletes, tournaments) 1 2 3 4 5 Politics (e.g., international relations, politicians, 1 2 3 4 5 elections, law)
What communicative functions do you use Weibo for? Please check the number that best reflects your Weibo posting activities, including posts, sharing, and comments you usually upload on Weibo.
I use Weibo to …
Never Rarely Someti Often Always mes Express my love for life, others, myself, etc. 1 2 3 4 5 Express my gratitude to family, friends, others, 1 2 3 4 5 the God, etc. Ask for support from friends, family, others, the 1 2 3 4 5 God, etc. Commemorate/remember people, special days, 1 2 3 4 5 events, etc. Complain about people, things, etc. 1 2 3 4 5 Express deep thoughts such as ideas, goals, 1 2 3 4 5 aspirations, etc. Entertain/occupy myself 1 2 3 4 5 Wish someone a happy birthday or other special 1 2 3 4 5 occasions.
Please check the number that best reflects your behaviors on Weibo.
Never Rarely Someti Often Always mes I provide false personal information when setting 1 2 3 4 5 up accounts on Weibo. I provide false information on my profile on 1 2 3 4 5 Weibo. I monitor my profiles on Weibo. 1 2 3 4 5 I am careful about the pictures of myself I post on 1 2 3 4 5 my Weibo profile. I am careful about whom I friend on Weibo. 1 2 3 4 5 I am careful about what groups I join on Weibo. 1 2 3 4 5 99
I un-tag pictures on Weibo. 1 2 3 4 5 I delete messages from my wall on Weibo. 1 2 3 4 5 I regularly review Weibo’s personal settings. 1 2 3 4 5 I control my privacy settings on Weibo so that 1 2 3 4 5 what I do on Weibo do not show up on my newsfeed. I control my privacy settings on Weibo so that 1 2 3 4 5 only my friends can see my profile. I use privacy controls to allow me to filter 1 2 3 4 5 which friends’ group sees different details of my profile on Weibo.
What information do you disclose on your Weibo profile and posts? Check all that apply.
a. Name, b. picture, c. Age, d. Gender, e. Birthday, f. country g. Address, h. Marital status, i. Telephone Number, j. School Attending k. Place of Employment, l. Love life (engaged, dating) m. Interest, n. Hobbies o. music favorites, p. movie favorites, q. favorite books, r. favorite TV shows, s. Friends, t. Social Activities, u. Tastes and preferences, v. Relationship Status, w. Sexual Preferences, x. Political Views, y. Religion, z. Family situation,
Finally, we would like to ask a few questions about yourself.
What is your gender? ( ) Male ( ) Female ( ) Other
In what year were you born? ( )
Where did you come from? 100
( ) Mainland China ( ) Hong Kong ( ) Taiwan ( ) Macau ( ) Others: please specify.
Have you used American SNSs (e.g., FaceBook, Twitter, YouTube, etc.) before coming to the U.S.? ( ) Yes ( ) No
Are you an undergraduate student or graduate student? ( ) Under graduate student ( ) Graduate Student (master’s program) ( ) Graduate Student (doctoral program)
How long have you lived in the United States? ( ) Years
You just answered the last question. Thank you very much for participating in this survey. If you would like to be entered for random drawings of $25 Amazon gift cards, please type your email address below:
You are reaffirming your consent by clicking a "submit" button. Please feel free to contact Kisun Kim ([email protected] | 419-819-9866) and Dr. Sung-Yeon Park ([email protected] | 419-372-4322) if you would like more information regarding this study.
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