Measuring node importance on Twitter microblogging

Social Networks (SN) are created whenever people interact with other people in online social networks, such as Twitter, Google+, Facebook and etc. Twitter is a social networking and micro-blogging service; it creates several new interesting social network structures. In this sense, our main goal is to investigate the power of retweet mechanism. The findings suggest that relations of "friendship" at Twitter are important but not enough. Still, the centrality measures of a node importance do not show how important users are. We uncovered some other principles that must be studied like, homophily phenomenon, the tendency of individuals to associate and bond with similar others.

[1]  Luís Sarmento,et al.  Characterization of the twitter @replies network: are user ties social or topical? , 2010, SMUC '10.

[2]  Yunli Wang,et al.  Automatic detecting indicators for quality of health information on the Web , 2007, Int. J. Medical Informatics.

[3]  Shyhtsun Felix Wu,et al.  Measuring message propagation and social influence on Twitter.com , 2010, Int. J. Commun. Networks Distributed Syst..

[4]  Stanley Wasserman,et al.  Social Network Analysis: Methods and Applications , 1994, Structural analysis in the social sciences.

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

[6]  Daniel Gayo-Avello,et al.  Nepotistic relationships in Twitter and their impact on rank prestige algorithms , 2010, Inf. Process. Manag..

[7]  Sang-Won Lee,et al.  On social Web sites , 2010, Inf. Syst..

[8]  Ying Fan,et al.  Identifying and Characterizing Nodes Important to Community Structure Using the Spectrum of the Graph , 2011, PloS one.

[9]  Junghoo Cho,et al.  Topical semantics of twitter links , 2011, WSDM '11.

[10]  Daniel M. Romero,et al.  Influence and Passivity in Social Media , 2011, ECML/PKDD.

[11]  Ramanathan V. Guha,et al.  Information diffusion through blogspace , 2004, WWW '04.

[12]  Scott Counts,et al.  Identifying topical authorities in microblogs , 2011, WSDM '11.

[13]  Daniel M. Romero,et al.  Influence and passivity in social media , 2010, ECML/PKDD.

[14]  Hiroyuki Kitagawa,et al.  TURank: Twitter User Ranking Based on User-Tweet Graph Analysis , 2010, WISE.

[15]  Judit Bar-Ilan,et al.  A method for measuring the evolution of a topic on the Web: The case of "informetrics" , 2009, J. Assoc. Inf. Sci. Technol..

[16]  Rajeev Motwani,et al.  The PageRank Citation Ranking : Bringing Order to the Web , 1999, WWW 1999.

[17]  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.

[18]  Amit P. Sheth,et al.  A Qualitative Examination of Topical Tweet and Retweet Practices , 2010, ICWSM.

[19]  M. Kilduff,et al.  The ties that lead: A social network approach to leadership , 2005 .

[20]  Yutaka Matsuo,et al.  How to Become Famous in the Microblog World , 2010, ICWSM.

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

[22]  Ed H. Chi,et al.  Want to be Retweeted? Large Scale Analytics on Factors Impacting Retweet in Twitter Network , 2010, 2010 IEEE Second International Conference on Social Computing.

[23]  Lisa Singh,et al.  Can Friends Be Trusted? Exploring Privacy in Online Social Networks , 2009, 2009 International Conference on Advances in Social Network Analysis and Mining.

[24]  Phillip Bonacich,et al.  Some unique properties of eigenvector centrality , 2007, Soc. Networks.

[25]  Danah Boyd,et al.  Tweet, Tweet, Retweet: Conversational Aspects of Retweeting on Twitter , 2010, 2010 43rd Hawaii International Conference on System Sciences.

[26]  Yang Wang,et al.  Detecting Important Nodes to Community Structure Using the Spectrum of the Graph , 2011, ArXiv.

[27]  Krishna P. Gummadi,et al.  Measuring User Influence in Twitter: The Million Follower Fallacy , 2010, ICWSM.

[28]  Ben Shneiderman,et al.  Analyzing Social Media Networks with NodeXL: Insights from a Connected World , 2010 .

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