DOCSLIB.ORG

A Method for Analysis of Node Position in the Network of Internet Users

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
A Method for Analysis of Node Position in the Network of Internet Users A Method for Analysis of Node Position in the Network of Internet Users Katarzyna Musia l Institute of Computer Science Wroclaw University of Technology Thesis submitted for the Degree of Doctor of Philosophy in the Wroclaw University of Technology · 2009 · Contents Acknowledgments xiii Important Symbols xiv Abbreviations xv Abstract xvi 1 Introduction 1 2 Social Networks 7 2.1 RegularSocialNetwork. 7 2.2 NetworkofInternetUsers . 14 2.2.1 Concept of the Network of Internet Users . 15 2.2.2 Taxonomy of the Networks of Internet Users . 19 2.3 Internet Identity — Node of the Network of Internet Users . 21 2.3.1 Concept of the Internet Identities . 21 2.3.2 Individual and Group Internet Identity . 26 2.3.3 Internet Identities Integration . 28 2.4 Internet Relationships — Edges of the Network of Internet Users 30 2.4.1 Concept of the Internet Relationship . 30 2.4.2 Types of the Internet Relationships . 31 2.4.3 Directness of the Internet Relationship . 34 i 2.4.4 Ties ............................ 36 2.5 Examples of the Networks of Internet Users . 38 2.5.1 Electronic Mail Services . 38 2.5.2 InstantMessengers . 38 2.5.3 BlogsServices....................... 39 2.5.4 Social Networking Sites . 39 2.5.5 Multimedia Sharing Systems . 40 2.5.6 AuctionSystems . .. .. 41 2.5.7 SocialSearchEngines. 42 2.5.8 Social Bookmarking and Cataloging . 42 2.5.9 Homepages ........................ 43 2.5.10 Knowledge Sharing Systems . 43 2.5.11 Virtual Worlds and Multiplayer Online Games . 44 2.5.12 Collaborative Authoring Systems — Wikis . 44 2.5.13 FriendOfAFriendProject . 45 2.5.14 Complex Communications Systems . 45 2.5.15 Comparison ........................ 45 3 User Position in Social Network 51 3.1 SocialNetworkAnalysis . 51 3.2 UserPosition ........................... 55 3.2.1 Prestige .......................... 55 3.2.2 Centrality ......................... 57 3.3 Comparison of the User Position Indices . 59 4 Node Position in Network of Internet Users 64 4.1 GeneralConcept ......................... 64 4.2 CommitmentEvaluation . 67 ii 4.3 NodePositionCalculation . 69 4.3.1 PINNodes......................... 70 4.3.2 PINEdges......................... 71 4.3.3 PINHybrid ........................ 72 4.4 Example of Node Position Calculation . 74 4.4.1 The Influence of ε ..................... 74 4.4.2 The Influence of Initial Node Positions . 79 4.4.3 The Convergence of Node Position Method . 80 4.4.4 Example — Conclusions . 83 5 Formal Analysis of the Node Position Method 84 5.1 TotalandAverageNodePosition . 84 5.2 Convergence............................ 86 5.3 IntervalofLimitValues . 89 6 Research 92 6.1 ThurmanNetwork ........................ 93 6.1.1 DataDescriptionandPreparation . 93 6.1.2 Comparison of Node Position with Other Centrality Methods.......................... 95 6.2 EnronNetwork .......................... 99 6.2.1 DataDescriptionandPreparation . 99 6.2.2 Characteristics ofNodePosition . 101 6.3 Wroclaw University of Technology Network . 106 6.3.1 DataDescription andPreparation . 106 6.3.2 Influence of stopping condition τ and ε coefficient . 106 6.3.3 Comparison with Other User Position Indices . 114 6.4 EfficiencyTests ..........................117 iii 6.4.1 Influence of ε on Processing Time . 117 6.4.2 Influence of Network Size on Processing Time . 118 6.4.3 Efficiency of Node Position versus Other User Position Indices...........................126 6.5 Possible Application of Node Position Method . 127 6.5.1 Method for Bridges’ Properties Analysis . 128 6.5.2 Experiments. .. .. .129 7 Conclusions and Future Work 134 References 138 Appendix A 149 Appendix B 151 Appendix C 161 iv List of Figures 2.1 Aregularsocialnetwork . .. .. 9 2.2 The division of social networks based on the type of the rela- tionship .............................. 12 2.3 An example of relationships between people working in a com- pany................................ 13 2.4 The division of social networks based on the type of the com- municationchannel . .. .. 13 2.5 Homogeneous HSN, system–based (SSN), and internet multi- modal social network (ISN) ................... 15 2.6 Examples of homogeneous HSN, system–based (SSN), and in- ternet multimodal social network (ISN) ............ 16 2.7 Realtimevs. nonrealtimenetworks . 20 2.8 Mapping of social entities into internet identities . 22 2.9 The concept of internet identities merging . 26 2.10 Integration of two system–based social networks by means of internet identity merging . 29 2.11 Taxonomy of internet relationships . 32 2.12 Thedirectionofrelationships[33] . 33 2.13 The direct internet relationship in the social network on the Internet .............................. 35 v 2.14 The quasi–direct internet realtionship in the social network on theInternet ............................ 35 2.15 The object–based internet relationship with equal roles: com- mentator (a), and different roles: commentator and author (b)................................. 36 2.16 The indirect internet relationship in the social network on the Internet .............................. 36 2.17 The tie concept in the social network . 37 2.18 Main functions of the social networking site related to rela- tionshipmaintenance . 40 3.1 Methods of social network analysis . 54 4.1 Example of the network of Internet users NIU with the as- signed commitment values . 65 4.2 Distribution of the commitment for an inactive member y equally among all y’sacquaintances . 66 4.3 The network of Internet users that can be extracted from the emailcommunication . 74 4.4 The values of members’ node positions in relation to ε value . 77 4.5 The value of social position in relation to ε ........... 78 4.6 The minimum, maximum, average, and standard deviation of node position calculated for the same community but for different values of ε ........................ 78 4.7 The linear regression for average node position and standard deviation.............................. 79 4.8 The values of node position after every iteration for ε = 0.95 . 81 vi 4.9 The values of the member x’s node position after every itera- tion for various ε ......................... 81 4.10 The convergence of the node position sum for various ε and variousinitialsums . .. .. 82 5.1 The community where individual x has the greatest node po- sition................................ 89 5.2 The chart of the function f(ε) for the network that consists of m Internetusers.......................... 91 5.3 Therangeofthenodepositionvalues . 91 6.1 Graph representation of the classic Thurman network . 93 6.2 The comparison of centrality measures to node position in the Thurmannetwork......................... 96 6.3 The comparison of prestige measures to node position in the Thurmannetwork......................... 96 6.4 The comparison of eigenvector measures with node position in theThurmannetwork ...................... 97 6.5 The values of Kendall’s coefficient for the pairs of rankings fromTable6.4...........................100 6.6 Average NP and NP wT F as well as their standard deviations in the Enron dataset, calculated for different values of ε . 102 6.7 The percentage of users with NP < 1 and NP ≥ 1 within the Enron network in relation to ε ..................102 6.8 The distribution of NP depending on ε .............103 6.9 Percentage of duplicates within the set of node measures, sep- arately for node position with different values of ε, degree prestige (IDC), and degree centrality (ODC) .........103 vii 6.10 The percentage contribution of members with NP ≥ NP wT F and NP < NP wT F within the Enron social network in rela- tion to ε ..............................105 6.11 The mean squared error between NP and NP wT F for the Enron dataset in relation to ε ..................106 6.12 Social network discovered from the email communication be- tween employees of WUT . 107 6.13 Processing time [min] of the PIN edges depending on different values of ε coefficient and stop condition τ ...........109 6.14 Processing time [min] of the PIN edges depending on different values of coefficient ε .......................109 6.15 Processing time [min] of the PIN edges depending on different value stop condition τ ......................110 6.16 Number of required iterations depending on different values of ε coefficient and stopping condition τ ..............111 6.17 Processing time [min] of the PIN edges depending on different values of ε coefficient and stop condition τ ...........112 6.18 Exponential fitting function for the relation between ε and numberofiterations . .113 6.19 Exponential fitting function for the relation between ε and numberofduplicates . .115 6.20 Processing time of the PIN nodes depending on different size ofnetwork.............................120 6.21 Processing time of the PIN edges depending on different size of network ..............................121 6.22 Processing time of the PIN hybrid depending on different size ofnetwork.............................122 viii 6.23 Processing time depending on the number of nodes in the net- workforfixednumber ofedges(50,000). 123 6.24 Processing time depending on the number of edges in the net- workforfixednumberofnodes(50,000) . 125 6.25 Crucial steps of the proposed method of bridges properties analysis ..............................128 6.26 Structure of peripheral nodes in Thurman network and bridges that connect PN with the regular cliques . 131 6.27 Structure of peripheral clique in Thurman network and bridges that connect PC with the regular cliques . 131 7.1 TherelationlayersinFlickr . .152 7.2 Relation layers extracted from contact lists: Rc (a), Rrc (b), and Rcoc (c)............................153
Load more

Recommended publications
  • Building a Scalable Index and a Web Search Engine for Music on the Internet Using Open Source Software
    Department of Information Science and Technology Building a Scalable Index and a Web Search Engine for Music on the Internet using Open Source software André Parreira Ricardo Thesis submitted in partial fulfillment of the requirements for the degree of Master in Computer Science and Business Management Advisor: Professor Carlos Serrão, Assistant Professor, ISCTE-IUL September, 2010 Acknowledgments I should say that I feel grateful for doing a thesis linked to music, an art which I love and esteem so much. Therefore, I would like to take a moment to thank all the persons who made my accomplishment possible and hence this is also part of their deed too. To my family, first for having instigated in me the curiosity to read, to know, to think and go further. And secondly for allowing me to continue my studies, providing the environment and the financial means to make it possible. To my classmate André Guerreiro, I would like to thank the invaluable brainstorming, the patience and the help through our college years. To my friend Isabel Silva, who gave me a precious help in the final revision of this document. Everyone in ADETTI-IUL for the time and the attention they gave me. Especially the people over Caixa Mágica, because I truly value the expertise transmitted, which was useful to my thesis and I am sure will also help me during my professional course. To my teacher and MSc. advisor, Professor Carlos Serrão, for embracing my will to master in this area and for being always available to help me when I needed some advice.
    [Show full text]
  • Problematic Internet Use in Adolescents: an Overview for Primary Care Providers Jasmine Atwal, M.D., Nicole Klaus, Ph.D., A.B.P.P., Rebecca Daily, M.D
    Kansas Journal of Medicine 2012 Problematic Internet Use Problematic Internet Use in Adolescents: An Overview for Primary Care Providers Jasmine Atwal, M.D., Nicole Klaus, Ph.D., A.B.P.P., Rebecca Daily, M.D. University of Kansas School of Medicine-Wichita Department of Psychiatry and Behavioral Sciences Introduction Technology use is playing an iated with psychosomatic symptoms such as increasingly important role in the daily lives lack of physical energy, weakened of adolescents. As many adolescents readily immunity, and lower life satisfaction.8 incorporate the internet into their lives, it is Excessive internet usage can be defined as important to be aware of the negative greater than or equal to 35 hours per week. 4 consequences that can stem from High levels of electronic media use by problematic internet use. adolescents, including internet overuse, is Problematic internet use is characterized related to poor sleep patterns and increased by an excessive preoccupation with internet daytime sleepiness, decreased level of use and a difficulty controlling urges and functioning during the day, and fatigue.9-11 behaviors related to the internet. 1 This Excessive time spent on the internet preoccupation with or use of the internet increases the opportunity to be victimized causes significant distress or impairment in through unwanted sexual solicitation, social, occupational, or other important exposure to pornography, and cyberbullying. areas of functioning.2 Though there is no One study 12 showed that 9% of youth listing of problematic internet use in the reported unwanted sexual solicitation, 11% Diagnostic and Statistical Manual of Mental of youth reported an online harassment Disorders (DSM-IV-TR),3 many articles experience (cyberbullying), and 23% of have proposed ways to identify when youth reported unwanted exposure to internet use has become a problem.
    [Show full text]
  • Does User Generated Content Characterize Millennials' Generation Behavior?
    Journal of Open Innovation: Technology, Market, and Complexity Article Does User Generated Content Characterize Millennials’ Generation Behavior? Discussing the Relation between SNS and Open Innovation Jose Ramon Saura 1 , Felipe Debasa 2 and Ana Reyes-Menendez 1,* 1 Department of Business Economics, Rey Juan Carlos University, 28032 Madrid, Spain; [email protected] 2 Education Sciences, Language, Culture and Arts, Historical-Legal and Humanistic Sciences and Modern Languages, Rey Juan Carlos University, 28032 Madrid, Spain; [email protected] * Correspondence: [email protected] Received: 12 August 2019; Accepted: 25 November 2019; Published: 26 November 2019 Abstract: The millennial generation plays a leading role in today’s connected world in which exists a confluence of numerous technologies and the internet in science, economy and innovation. This study aimed to identify the key factors that characterize the millennial generation within the online chatter on Twitter using an innovative approach. To this end, we analyzed the user generated content (UGC) in the social network (SNS) Twitter using a three-steps knowledge-based method for information management. In order to develop this method, we first used latent Dirichlet allocation (LDA), a state-of-the-art thematic modeling tool that works with Python, to analyze topics in our database. The data were collected by extracting tweets with the hashtag #Millennial, #Millennials and #MillennialGeneration on Twitter (n = 35,401 tweets). Secondly, sentiment analysis with a support vector machine (SVM) algorithm was also developed using machine-learning. Applying this method to the LDA results resulted in the categorization of the topics into those that contained negative, positive and neutral sentiments.
    [Show full text]
  • Wikia Search: La Transparencia Es Un Arma Cargada De Futuro Por Fabrizio Ferraro
    Wikia search: la transparencia es un arma Cargada de futuro Por Fabrizio Ferraro Lo que hace de Wikia Search un proyecto potencialmente innovador no es ni la intervención del Claves factor humano ni la calidad de los resultados de las búsquedas. Su posible ventaja competitiva es la transparencia, que podría convertirlo en el buscador más 1 Wikia Search se basa en el concepto del wiki, un término fiable en cuanto a la neutralidad de sus resultados. que designa a las sedes web que se nutren de los Sin embargo, Wikia Search no ha empezado con buen pie. contenidos que aportan los propios usuarios. El ejemplo “Una de las mayores decepciones que he tenido la de wiki más célebre es desgracia de tener que comentar”, se afirma en la crítica Wikipedia, que Nielsen situaba en noveno lugar en el del influyente blog de tecnología TechCrunch. La mayoría ranking de sedes más de artículos de la prensa y de los blogs reflejan visitadas por los internautas sentimientos parecidos. Es una reacción chocante por estadounidenses a finales de 2007. cuanto han sido estos mismos medios los que han creado más expectativas sobre el nuevo motor de búsqueda “social” llamado a disputarle el trono a Google. El buscador de Wikia 2 Search utiliza tecnología de Las críticas se han ensañado especialmente con los código abierto que, paupérrimos resultados que arroja el nuevo motor de contrariamente a la que utilizan sus rivales, permite a búsqueda en comparación con los que ofrece Google. los propios usuarios aportar Tampoco ha gustado que la tan cacareada intervención mejoras a los algoritmos que humana en la ordenación de los resultados no esté ordenan los resultados del buscador.
    [Show full text]
  • Examination of Communication and Social Media Usage Among Socially Anxious Individuals Greyson K
    University of Mississippi eGrove Honors College (Sally McDonnell Barksdale Honors Theses Honors College) 2019 Examination of Communication and Social Media Usage among Socially Anxious Individuals Greyson K. Young University of Mississippi Follow this and additional works at: https://egrove.olemiss.edu/hon_thesis Part of the Psychology Commons Recommended Citation Young, Greyson K., "Examination of Communication and Social Media Usage among Socially Anxious Individuals" (2019). Honors Theses. 1125. https://egrove.olemiss.edu/hon_thesis/1125 This Undergraduate Thesis is brought to you for free and open access by the Honors College (Sally McDonnell Barksdale Honors College) at eGrove. It has been accepted for inclusion in Honors Theses by an authorized administrator of eGrove. For more information, please contact [email protected]. EXAMINATION OF COMMUNICATION AND SOCIAL MEDIA USAGE AMONG SOCIALLY ANXIOUS INDIVIDUALS by Greyson K. Young A thesis submitted to the faculty of The University of Mississippi in partial fulfillment of the requirements of the Sally McDonnell Barksdale Honors College. Oxford April 2019 Approved by: _____________________________ Advisor: Professor Laura J. Dixon ____________________________ Reader: Professor Carrie V. Smith ___________________________ Reader: Professor Lee M. Cohen SOCIAL MEDIA USE AND SOCIAL ANXIETY ii © 2019 Greyson K. Young ALL RIGHTS RESERVED ii SOCIAL MEDIA USE AND SOCIAL ANXIETY iii Abstract Social anxiety disorder (SAD) affects between 6.8% and 12.1% of the U.S. population. At the core of SAD is the fear of social situations, and in particular, the fear of others’ positive (FPE) and negative (FNE) evaluation. Studies have found that social media and online/indirect communication are commonly used to minimize the experience of stress, anxiety, evaluation, and rejection commonly associated with face-to-face interactions.
    [Show full text]
  • Facebook Addiction and Life Satisfaction
    Facebook Addiction And Life Satisfaction Floatiest Vasilis venturings unmindfully. Electrotonic Andonis revile deadly while Fitz always frights his parterre enfaces redolently, he kyanizing so infrangibly. Ideological and fenestrated Sonny germinating her sleazes quartzite filed and demarcated ineffably. Gpa was found to satisfaction among young adult chatting, life satisfaction might have increased life satisfaction? Asare A, and scrolling, and psychosocial status. In some case studies have free time away to mental health problems in chat rooms or maybe you! In gym last decade, online social networking has caused profound changes in aisle way he communicate negotiate interact. On fb and negative behavioral sciences, said to qualitative analyses, presenting both addictions such articles here, rewritten or unhappy? Bfas retained one could have facilitated or would change, life and facebook addiction satisfaction were asked for more conscientious than ever before bed later on social media networking sites use varies across outcomes. Company or expand their online. Now with life satisfaction changes its effects has increased life satisfaction: results of other beneficial. London rooms and online worldwide. Facebook has taken as and how can leave you helping you in college students are growing phenomenon and facebook addiction and life satisfaction with life satisfaction? There is sustain a significant relationship, using a holding of undergraduate students. These cues and satisfaction and life and facebook addiction satisfaction, we even see significant differences between personality traits and advocate on social. Nonetheless, since the next wave might be some usage. During literature sheds light screens at least. Despite this limitation, BÅ‚aszkiewicz K, Griffiths MD: Social Networking Sites and Addiction: Ten Lessons Learned.
    [Show full text]
  • I. Hidden Features of the Major Search Engines
    “When librarians rule the world: the skills and tools we need to thrive in a Web 2.0 world” Presentation by Mary Ellen Bates , www.BatesInfo.com , held on 29 th February 2008, Zentral- und Landesbibliothek Berlin Compiled by Anke Bruns¹ and Susanne Schaper² ¹MPDL, Munich / GWDG, Göttingen, [email protected] ²MPI for terrestrial Microbiology, Marburg, [email protected] As Mary Ellen Bates’ presentation was only available on paper and not on the web, we have put together much of her information in this report, using her own structure and headings. The URLs mentioned were functional on 7 April 2008. Content: “When librarians rule the world: the skills and tools we need to thrive in a Web 2.0 world”................................................................................................................................. 1 I. Hidden features of the major search engines........................................................................ 1 A. Google's secrets ............................................................................................................ 1 B. Yahoo's secrets ............................................................................................................. 2 C. Live.com's Secrets ........................................................................................................ 3 II. Specialized and lesser-known search engines................................................................... 4 III. Creating your own search engine.....................................................................................
    [Show full text]
  • Search Engines and Power: a Politics of Online (Mis-) Information
    5/2/2020 Search Engines and Power: A Politics of Online (Mis-) Information Webology, Volume 5, Number 2, June, 2008 Table of Titles & Subject Authors Home Contents Index Index Search Engines and Power: A Politics of Online (Mis-) Information Elad Segev Research Institute for Law, Politics and Justice, Keele University, UK Email: e.segev (at) keele.ac.uk Received March 18, 2008; Accepted June 25, 2008 Abstract Media and communications have always been employed by dominant actors and played a crucial role in framing our knowledge and constructing certain orders. This paper examines the politics of search engines, suggesting that they increasingly become "authoritative" and popular information agents used by individuals, groups and governments to attain their position and shape the information order. Following the short evolution of search engines from small companies to global media corporations that commodify online information and control advertising spaces, this study brings attention to some of their important political, social, cultural and economic implications. This is indicated through their expanding operation and control over private and public informational spaces as well as through the structural bias of the information they attempt to organize. In particular, it is indicated that search engines are highly biased toward commercial and popular US- based content, supporting US-centric priorities and agendas. Consequently, it is suggested that together with their important role in "organizing the world's information" search engines
    [Show full text]
  • The Relational Reconnection Function of Social Network Sites
    View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Trinity University Trinity University Digital Commons @ Trinity Human Communication and Theatre Faculty Research Human Communication and Theatre 6-2017 The Relational Reconnection Function of Social Network Sites Artemio Ramirez Jr. Erin M. Bryant Trinity University, [email protected] John Spinda Follow this and additional works at: https://digitalcommons.trinity.edu/hct_faculty Part of the Theatre and Performance Studies Commons Repository Citation Ramirez, A., Jr., Sumner, E. M., & Spinda, J. (2017). The relational reconnection function of social network sites. New Media & Society, 19(6), 807-825. doi: 10.1177/1461444815614199 This Post-Print is brought to you for free and open access by the Human Communication and Theatre at Digital Commons @ Trinity. It has been accepted for inclusion in Human Communication and Theatre Faculty Research by an authorized administrator of Digital Commons @ Trinity. For more information, please contact [email protected]. Friendships and SNS Reconnection 1 ABSTRACT Relational reconnection is a prominent yet under-explored function of social network sites (SNS) that encompasses both the activation and subsequent maintenance of dormant social ties. The present investigation used two data collections (Study 1, six university sample; Study 2, national United States sample) to explore the characteristics of friends who reconnect using SNS, and attempt to predict whether reconnected relationships persisted beyond the initial reconnection. Results indicated that relational reconnection is extremely common, especially among same-sex friends and individuals who identify as heavy SNS users. Predicted outcome value emerged as the best predictor of persistence beyond initial reconnection, in addition to engaging in modality expansion, being female, and reactivating a relationship with greater perceived development pre- loss-of-contact.
    [Show full text]
  • The Commodification of Search
    San Jose State University SJSU ScholarWorks Master's Theses Master's Theses and Graduate Research 2008 The commodification of search Hsiao-Yin Chen San Jose State University Follow this and additional works at: https://scholarworks.sjsu.edu/etd_theses Recommended Citation Chen, Hsiao-Yin, "The commodification of search" (2008). Master's Theses. 3593. DOI: https://doi.org/10.31979/etd.wnaq-h6sz https://scholarworks.sjsu.edu/etd_theses/3593 This Thesis is brought to you for free and open access by the Master's Theses and Graduate Research at SJSU ScholarWorks. It has been accepted for inclusion in Master's Theses by an authorized administrator of SJSU ScholarWorks. For more information, please contact [email protected]. THE COMMODIFICATION OF SEARCH A Thesis Presented to The School of Journalism and Mass Communications San Jose State University In Partial Fulfillment of the Requirement for the Degree Master of Science by Hsiao-Yin Chen December 2008 UMI Number: 1463396 INFORMATION TO USERS The quality of this reproduction is dependent upon the quality of the copy submitted. Broken or indistinct print, colored or poor quality illustrations and photographs, print bleed-through, substandard margins, and improper alignment can adversely affect reproduction. In the unlikely event that the author did not send a complete manuscript and there are missing pages, these will be noted. Also, if unauthorized copyright material had to be removed, a note will indicate the deletion. ® UMI UMI Microform 1463396 Copyright 2009 by ProQuest LLC. All rights reserved. This microform edition is protected against unauthorized copying under Title 17, United States Code. ProQuest LLC 789 E.
    [Show full text]
  • Ways to Protect Students from Online Predators
    Academic Exchange Quarterly Spring 2014 ISSN 1096-1453 Volume 18, Issue 1 To cite, use print source rather than this on- line version which does not reflect print copy f o rmat . Anyone may view, reproduce or store copy of this article for personal, non-commercial use as allowed by the "Fair Use" limitations (sections 107 and 108) of the U.S. Copyright law. See also electronic version copyright clearance http://rapidintellect.com/AEQweb/macacl.htm Ways To Protect Students From Online Predators Timothy Baghurst, Oklahoma State University Rodney Alexander, Defense Information Systems Agency Tyler Tapps, Oklahoma State University Drs. Baghurst and Tapps are assistant professors in the School of Applied Health and Educational Psychology at Oklahoma State University. Dr. Alexander is in Joint Interoperability Test Command with the Defense Information Systems Agency. Abstract This study explored teacher and counselors’ perceptions of how to prevent adolescents from internet sexual predators. Twenty-five teachers and counselors were interviewed, and lack of parental support and access to social networking websites were the primary circumstances leading to teenage internet sexual assault. Teen needs and gratification fostered t h e ir encounters with predators on the internet. Participants viewed greater parental supervision as necessary during internet use to limit possible contact with potential predators. Practical suggestions are provided for those working with students. Introduction The internet has become very important in society; it is present in the majority of households in America, but it is also becoming a new venue particularly for child sexual predators (Livingston, Haddon, & Görzig, 2012; Wolak, Finkelhor, Mitchell, & Ybarra, 2010).
    [Show full text]
  • The Megan Meier Myspace Suicide: a Case Study Exploring the Social
    The Megan Meier MySpace Suicide: A case study exploring the social aspects of convergent media, citizen journalism, and online anonymity and credibility By: Jacqueline Vickery M.A. student, University of Texas at Austin, Dept. of Radio-TV-Film In his book, Convergence Culture, Henry Jenkins explores the changing relationship between media audiences, producers, and content, in what he refers to as convergence media. These changes are not only evidenced by changes in technology, but rather involve social changes as well. As historian Lisa Gitelman says, a medium is not merely a communication technology, but also a set of cultural and social practices enabled by the medium. The internet, as a medium, challenges traditional top-down approaches to traditional news gathering and reporting by affording opportunities for “average citizens” to participate in the journalistic process. Anyone with access to a computer and an internet connection can, in theory, participate in the journalistic process by gathering information, offering an alternative opinion, and engaging in dialog via message boards and blogs. However, a social concept entwined within this practice is the formation of disembodied communities and identities, in which participants can opt to remain anonymous. Such anonymity brings to the surface new questions of credibility, questions which seem to have few, if any, definitive answers as of yet. I will be examining the Megan Meier MySpace “hoax”1 as it has been dubbed by the media, as evidence of convergence media, and as an entry point into the unintended consequences of citizen journalism and online anonymity. As I write this, many questions and allegations are still circulating in regards to exactly what events transpired the month leading up to Megan’s suicide, who was involved, and what the legal repercussions (if 1 I am reluctant to use the word “hoax” to describe an event that resulted in the death of a 13 year-old girl, but since that is how the media most often refers to it, I will stick to that language.
    [Show full text]