Information Overload, Similarity, and Redundancy: Unsubscribing Information Sources on Twitter

The emergence of social media has changed individuals' information consumption patterns. The purpose of this study is to explore the role of information overload, similarity, and redundancy in unsubscribing information sources from users' information repertoires. In doing so, we randomly selected nearly 7,500 ego networks on Twitter and tracked their activities in 2 waves. A multilevel logistic regression model was deployed to test our hypotheses. Results revealed that individuals egos obtain information by following a group of stable users alters. An ego's likelihood of unfollowing alters is negatively associated with their information similarity, but is positively associated with both information overload and redundancy. Furthermore, relational factors can modify the impact of information redundancy on unfollowing.

[1]  C. Sunstein.  Republic.com 2.0 , 2007 .

[2]  Albert,et al.  Emergence of scaling in random networks , 1999, Science.

[3]  Elaine J. Yuan,et al.  NEWS CONSUMPTION ACROSS MULTIPLE MEDIA PLATFORMS , 2011 .

[4]  Haewoon Kwak,et al.  Fragile online relationship: a first look at unfollow dynamics in twitter , 2011, CHI.

[5]  Haewoon Kwak,et al.  More of a Receiver Than a Giver: Why Do People Unfollow in Twitter? , 2012, ICWSM.

[6]  Jeffrey M. Quinn,et al.  Habits in everyday life: thought, emotion, and action. , 2002, Journal of personality and social psychology.

[7]  Gerard Salton,et al.  A vector space model for automatic indexing , 1975, CACM.

[8]  Jure Leskovec,et al.  The bursty dynamics of the Twitter information network , 2014, WWW.

[9]  M. McPherson,et al.  Birds of a Feather: Homophily in Social Networks , 2001 .

[10]  Stephen E. Robertson,et al.  Understanding inverse document frequency: on theoretical arguments for IDF , 2004, J. Documentation.

[11]  D. Murthy.  Towards a Sociological Understanding of Social Media: Theorizing Twitter , 2012 .

[12]  Hsiang Iris Chyi,et al.  News and the Overloaded Consumer: Factors Influencing Information Overload Among News Consumers , 2012, Cyberpsychology Behav. Soc. Netw..

[13]  A. Hermida,et al.  SHARE, LIKE, RECOMMEND , 2012 .

[14]  Bo Xu,et al.  Structures of broken ties: exploring unfollow behavior on twitter , 2013, CSCW.

[15]  Duncan J. Watts,et al.  Who says what to whom on twitter , 2011, WWW.

[16]  Reijo Savolainen,et al.  Filtering and withdrawing: strategies for coping with information overload in everyday contexts , 2007, J. Inf. Sci..

[17]  Jimmy J. Lin,et al.  Information network or social network?: the structure of the twitter follow graph , 2014, WWW.

[18]  Melanie Grunwald,et al.  Convergence Culture Where Old And New Media Collide , 2016 .

[19]  Heike Franz,et al.  The impact of computer mediated communication on information overload in distributed teams , 1999, Proceedings of the 32nd Annual Hawaii International Conference on Systems Sciences. 1999. HICSS-32. Abstracts and CD-ROM of Full Papers.

[20]  Su Jung Kim,et al.  A repertoire approach to cross-platform media use behavior , 2016, New Media Soc..

[21]  Jacob J. Wakshlag,et al.  A THEORY OF TELEVISION PROGRAM CHOICE , 1983 .

[22]  Z. J. Yang,et al.  ANTECEDENTS OF ONLINE INFORMATION SEEKING , 2013 .

[23]  Mor Naaman,et al.  The impact of network structure on breaking ties in online social networks: unfollowing on twitter , 2011, CHI.

[24]  Hai Liang,et al.  Testing Propositions Derived from Twitter Studies: Generalization and Replication in Computational Social Science , 2015, PloS one.

[25]  J. G. Webster.  The Marketplace of Attention: How Audiences Take Shape in a Digital Age , 2014 .

[26]  Ee-Peng Lim,et al.  Influentials, Novelty, and Social Contagion: The Viral Power of Average Friends, Close Communities, and Old News , 2012, Soc. Networks.

[27]  Daniel Kreiss,et al.  The Marketplace of Attention : How Audiences Take Shape in a Digital Age , 2016 .

[28]  Daniele Quercia,et al.  Loosing "friends" on Facebook , 2012, WebSci '12.

[29]  Qi He,et al.  TwitterRank: finding topic-sensitive influential twitterers , 2010, WSDM '10.

[30]  France Bélanger,et al.  Communication Media Repertoires: Dealing with the Multiplicity of Media Choices , 2007, MIS Q..

[31]  Scott A. Golder,et al.  Structural Predictors of Tie Formation in Twitter: Transitivity and Mutuality , 2010, 2010 IEEE Second International Conference on Social Computing.

[32]  Harsh Taneja,et al.  Media consumption across platforms: Identifying user-defined repertoires , 2012, New Media Soc..

[33]  Keri K. Stephens,et al.  Organizational Communication in Emergencies: Using Multiple Channels and Sources to Combat Noise and Capture Attention , 2013 .

[34]  Douglas A. Ferguson,et al.  The World Wide Web as a Functional Alternative to Television , 2000 .

[35]  Hosung Park,et al.  What is Twitter, a social network or a news media? , 2010, WWW '10.

[36]  Mohan J. Dutta-Bergman.  Complementarity in Consumption of News Types Across Traditional and New Media , 2004 .

[37]  Anne Bowser,et al.  PLAYING IN THE SAME TWITTER NETWORK , 2013 .

[38]  Ali F. Farhoomand,et al.  Managerial information overload , 2002, CACM.

[39]  Robert S. Stawski,et al.  Multilevel Analysis: An Introduction to Basic and Advanced Multilevel Modeling (2nd Edition) , 2013 .

[40]  J. G. Webster.  User information regimes: How social media shape patterns of consumption , 2010 .

[41]  Thomas B. Ksiazek,et al.  The Dynamics of Audience Fragmentation: Public Attention in an Age of Digital Media , 2012 .

[42]  Shinichi Nakagawa,et al.  A general and simple method for obtaining R2 from generalized linear mixed‐effects models , 2013 .

[43]  Danah Boyd,et al.  I tweet honestly, I tweet passionately: Twitter users, context collapse, and the imagined audience , 2011, New Media Soc..