A study of homophily on social media

The fact that similarity breeds connections, the principle of homophily, has been well-studied in existing sociology literature. Several studies have observed this phenomenon by conducting surveys on human subjects. These studies have concluded that new ties are formed between similar individuals. This phenomenon has been used to explain several socio-psychological concepts such as, segregation, community development, social mobility, etc. However, due to the nature of these studies and limitations because of involvement of human subjects, conclusions from these studies are not easily extensible in online social media. Social media, which is becoming the infinite space for interactions, has exceeded all the expectations in terms of growth, for reasons beyond human mind. New ties are formed in social media in the same way that they emerge in real-world. However, given the differences between real world and online social media, do the same factors that govern the construction of new ties in real world also govern the construction of new ties in social media? In other words, does homophily exist in social media? In this article, we study this extremely significant question. We propose a systematic approach by studying three online social media sites, BlogCatalog, Last.fm, and LiveJournal and report our findings along with some interesting observations. The results indicate that the influence of interest-based homophily is not a very strong leading factor for constructing new ties specifically in the three social media sites with implications to strategic advertising, recommendations, and promoting applications at large.

[1]  M. Newman,et al.  Finding community structure in very large networks. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.

[2]  L. Verbrugge The Structure of Adult Friendship Choices , 1977 .

[3]  Yun Chi,et al.  Blog Community Discovery and Evolution Based on Mutual Awareness Expansion , 2007, IEEE/WIC/ACM International Conference on Web Intelligence (WI'07).

[4]  Ulrike von Luxburg,et al.  A tutorial on spectral clustering , 2007, Stat. Comput..

[5]  Jon M. Kleinberg,et al.  Feedback effects between similarity and social influence in online communities , 2008, KDD.

[6]  Albert-László Barabási,et al.  Statistical mechanics of complex networks , 2001, ArXiv.

[7]  D. Hoyt,et al.  Adult Kinship Networks: The Selective Formation of Intimate Ties with Kin , 1983 .

[8]  A. B. M. S. Ali,et al.  Dynamic and Advanced Data Mining for Progressing Technological Development: Innovations and Systemic Approaches , 2009 .

[9]  Min Song,et al.  Handbook of Research on Text and Web Mining Technologies , 2008 .

[10]  Ferenc Bodon,et al.  A fast APRIORI implementation , 2003, FIMI.

[11]  Michael I. Jordan,et al.  Latent Dirichlet Allocation , 2001, J. Mach. Learn. Res..

[12]  Christian Rauh,et al.  The Influence of the Avatar on Online Perceptions of Anthropomorphism, Androgyny, Credibility, Homophily, and Attraction , 2005, J. Comput. Mediat. Commun..

[13]  Jan Rauch,et al.  Data Mining and Medical Knowledge Management: Cases and Applications , 2009 .

[14]  Matthew Richardson,et al.  Yes, there is a correlation: - from social networks to personal behavior on the web , 2008, WWW.

[15]  Vipin Kumar,et al.  A Fast and High Quality Multilevel Scheme for Partitioning Irregular Graphs , 1998, SIAM J. Sci. Comput..

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

[17]  Andrew B. Kahng,et al.  New spectral methods for ratio cut partitioning and clustering , 1991, IEEE Trans. Comput. Aided Des. Integr. Circuits Syst..

[18]  Lada A. Adamic,et al.  Friends and neighbors on the Web , 2003, Soc. Networks.

[19]  Richong Zhang,et al.  Opinion helpfulness prediction in the presence of “words of few mouths” , 2011, World Wide Web.

[20]  Huan Liu,et al.  Synthesis Lectures on Data Mining and Knowledge Discovery , 2009 .

[21]  S.,et al.  An Efficient Heuristic Procedure for Partitioning Graphs , 2022 .

[22]  Igor Kononenko,et al.  Influence of Domain and Model Properties on the Reliability Estimates' Performance , 2009, Int. J. Data Warehous. Min..

[23]  Ravi Kumar,et al.  On the Bursty Evolution of Blogspace , 2003, WWW '03.

[24]  D. Watts,et al.  Origins of Homophily in an Evolving Social Network1 , 2009, American Journal of Sociology.

[25]  Luca Cagliero,et al.  Analyzing twitter user- generated content changes , 2013 .

[26]  Michael J. Pazzani,et al.  A Framework for Collaborative, Content-Based and Demographic Filtering , 1999, Artificial Intelligence Review.

[27]  Mike Thelwall,et al.  Homophily in MySpace , 2009, J. Assoc. Inf. Sci. Technol..

[28]  P. Lazarsfeld,et al.  Friendship as Social process: a substantive and methodological analysis , 1964 .

[29]  Vishal Bhatnagar,et al.  Data Mining in Dynamic Social Networks and Fuzzy Systems , 2013 .

[30]  Thomas Hofmann,et al.  Probabilistic latent semantic indexing , 1999, SIGIR '99.

[31]  Andrea Tagarelli XML Data Mining: Models, Methods, and Applications , 2011 .

[32]  Bruce Hendrickson,et al.  A Multi-Level Algorithm For Partitioning Graphs , 1995, Proceedings of the IEEE/ACM SC95 Conference.

[33]  Fotis Lazarinis Retrieving Non-Latin Information in a Latin Web: The Case of Greek , 2009 .

[34]  A. Kaplan,et al.  Users of the world, unite! The challenges and opportunities of Social Media , 2010 .

[35]  Ali Serhan Koyuncugil,et al.  Financial Early Warning System for Risk Detection and Prevention from Financial Crisis , 2011 .

[36]  Eric Gilbert,et al.  Predicting tie strength with social media , 2009, CHI.

[37]  Inderjit S. Dhillon,et al.  Weighted Graph Cuts without Eigenvectors A Multilevel Approach , 2007, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[38]  M E J Newman,et al.  Community structure in social and biological networks , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[39]  Jitendra Malik,et al.  Normalized cuts and image segmentation , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[40]  Ying Zhou,et al.  Community discovery and analysis in blogspace , 2006, WWW '06.

[41]  Judith S. Donath,et al.  Homophily in online dating: when do you like someone like yourself? , 2005, CHI Extended Abstracts.