Copyright © 2013 Peyina Lin
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Copyright © 2013 Peyina Lin Channeling Friendships across Social Types via Mediated Communication and High School Clubs by Peyina Lin A dissertation Submitted in partial fulfillment of the Requirements for the degree of Doctor of Philosophy University of Washington 2013 Reading Committee: Michael B. Eisenberg, Chair David W. McDonald Katherine Stovel Ricardo Gomez Program Authorized to Offer Degree: The Information School University of Washington Abstract Channeling Friendships across Social Types via Mediated Communication and High School Clubs Peyina Lin Chair of the Supervisory Committee: Professor and Dean Emeritus Michael B. Eisenberg Information School This dissertation is about how common contexts for extracurricular activities, friendships, and technology mediated interactions form social structures that are related to distinct civic experiences of high school youth from diverse social types. A key role of education is to prepare individuals to participate in civil society. Extracurricular and civic experiences during high school contribute to such preparation because they are associated to civic participation in adulthood. Yet, participation opportunities for students are unequal. Research suggests that adolescents of diverse social types (i.e., categorical labels based on behavior stereotypes that students place on each other, like “Jocks” or “Gamers”) are predisposed to different activities. Extracurricular participation is further constrained by concerns for social validation (e.g., underperforming to not be labeled “Nerd”). Today, such social processes are increasingly mediated by communication technologies and social media. Despite the importance of social types, extracurricular activities or school clubs, friendships, and technologies in adolescents’ social development, little is known about their synergistic influences, the social structures they create, and how such structures affect civic experiences. In this dissertation, I compare such phenomena across two high schools. Based on 315 surveys, 26 interviews and observations collected over 10 months, I found that there are potentially optimal social structures for adolescents’ development of civic experiences; that the existence of multiple domain-specific school clubs, particularly in Science Technology Engineering and Math (STEM) and community service, was critical to the distinct social structures observed in each school; and that when the social structures were based on mediated interactions via different technologies (e.g., texting, instant messaging), specific affordances were revealed, about technologies and activity contexts, that helped make sense of how sub- communities select a communication technology to maintain needed group boundaries while use others to remain connected to their broader community. Using established methods in social network analysis, I examine the common contexts shared by social types. Adopting an information perspective, I describe how social information, such as values and norms, is channeled across social types via their common contexts of shared friendships or school clubs. I also assess the potential for such channels to bridge social divisions. Observed social structures corroborated students’ perceptions of social divisions, and the desire (or lack thereof) by social types from each school to participate in civic activities. I conclude first, with implications for schools to plan for broader civic participation according to the observed social structures. Then, I address the need for researchers to use social interaction data from more than one technology medium to make conclusions about social structure. Finally, I discuss design opportunities and challenges for supporting sub-communities’ needs to reify their group boundaries through a preferred technology while maintaining some connection to other groups. These implications for schools, research methods, and technology design, speak to the major concerns in information science: on the development of STEM and civics as part of life-long learning, on assessing research methods to study the vast availability of online data, and on novel design directions. DEDICATION I dedicate this dissertation to Ed and Aiden. With you, any journey is possible and much more enjoyable. i ACKNOWLEDGEMENTS This dissertation was partially funded by a 2009 NSF dissertation improvement grant from the Sociology Program (award # SES-0927291), a 2012 University of Washington Graduate School Presidential Fellowship, and a seed doctoral research grant from the Information School. I would like to thank Mike Eisenberg, Chair of my committee, for his continuous support. He has been a constant positive energy supplier. Without him, I would not have been able to gain access to the high schools from which I collected data. Mike also helped me get Microsoft Zunes for a student raffle, and supported my progress morally and financially. Thanks also to David W. McDonald and Kate Stovel for their advice, for asking hard questions, and helping me frame my research for specific communities. Thanks David for pushing me to move beyond “ICTs” thinking, for helping me frame my work for the CSCW community, and for helping me make my design implications more approachable to technology designers. Thanks to Kate for her feedback on my NSF dissertation proposal, without which I would not have won my NSF dissertation award. Kate also introduced me to seminal work on network thinking, upon which much of my work is grounded, and suggested various data analysis methods. Thanks to Lynne Manzo, my GSR, for her detailed proofreading of my written dissertation. Thanks to Ricardo Gomez, internal reader, for willing to join my committee in the last couple of months, and for his thoughtful questions. Reducing my committee members’ contributions to such few words is unfair and insufficient, but I hope it conveys a bit of my gratitude towards them. Thanks to the School District, teachers, staff, and students (and their parents) for participating in my dissertation. I am not naming them all to protect students’ privacy, as agreed in the Human Subjects application. This dissertation has also received advice or assistance from other individuals and departments at the University of Washington, including Marine Bahnsen, with assistance in R-coding; Hil Lyons from the Center for Statistical Consulting (CSC), iii Department of Statistics; and Stephanie Lee and her colleagues at the Center for Social Science Computation and Research (CSSCR). This dissertation has also benefited from teachings and/or advice from various individuals outside the University of Washington. I participated in the LINKS 2010 Center Summer Workshop on Social Network Analysis, housed in the Gatton College of Business and Economics at the University of Kentucky. There, Dan Halgin, Rich DeJordy Steve Borgatti and his team of Teaching Assistants, including Virginia Kidwell provided teachings and advice. Thanks to Steve Borgatti specifically for responding quickly to my UCINET bug reports and questions, along with Martin Everett. Thanks also to members of the INSNA listserv who responded to many of my inquiries. What a great community of smart scholars! Thanks to Ronald E. Rice and Hyo Kim for answering my questions about the methods they used in their paper Journal of Computer-Mediated Communication paper “Configurations of Relationships in Different Media: FtF, Email, Instant Messenger, Mobile Phone, and SMS,” which I was very happy to have found during the time I was analyzing my data. During the time I was developing my dissertation proposal, I also benefitted from wonderful discussions, albeit brief and via email, with various researchers. Molly W. Andolina, Professor in Political Science at DePaul University, and Cliff Zukin, Professor of Public Policy and Political Science at Rutgers’ Edward J. Bloustein School of Planning and Policy, discussed conceptualizations of civic engagement with me. Roberta Garner, Professor in Sociology at DePaul University shared her survey on adolescent cultures with me. Although my research did not draw on such survey, I thank her for her willingness to share. B. Bradford Brown referred me to relevant articles and answered questions via email about his STR (Social Type Rating manual), which although I did not adopt fully, when developing my survey, I consulted and used many of the social types in the STR. Work-in-progress from this dissertation has also been presented at various doctoral consortia, including CSCW ’11, iConference ’10, and CHI ‘09. Although the dissertation might not have gone in the directions discussed in these consortia, the exposure was nevertheless a valuable part of the process. Thanks to the advisors at such doctoral consortia. My PhD student peers have also been tremendous supporters at all stages of my dissertation. Thanks to my proposal writing support group (Oknam Park, Sunny Consolvo, and Phil Edwards), and peers who have at one point or another discussed any aspect of my data analysis or provided any other feedback (Ammy Jiranida Phuwarnartnurak, Gifford Cheung, Parmit Chilana, Jeff Hemsley, Jeff Huang, Shaun Kane, Shawn Walker, and others, who I may have left out for my aging memory). I also thank my former committee members Jens Eric Mai and Batya Friedman. I am sure one way or another, they have influenced my thinking. Thanks also to former and current staff at the iSchool from finance (Ty Ngo, Chanthala, and Dora), HR (Alisha, Crystal), research, and IT (Joshua Ayson, Scott Barker, Andy Gravano,