Two types of well followed users in the followership networks of Twitter

PLoS ONE

Volumn 9, Issue 1, 2014, Pages

  Saito, Kodai ^a   Masuda, Naoki ^a  

^a UNIVERSITY OF TOKYO   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; ARTICLE; ASIAN; CAUCASIAN; CONTROLLED STUDY; FOLLOWERSHIP; FRIEND; HUMAN; INFORMATION SERVICE; INTERNET; JAPANESE; KOREAN; RUSSIAN; SOCIAL NETWORK; TEXT MESSAGING; TWEET; TWITTER; TWITTER USER;

AREA UNDER CURVE; CLUSTER ANALYSIS; FRIENDS; HUMANS; INTERNET; SOCIAL NETWORKING;

EID: 84897424732     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0084265     Document Type: Article

References (24)

1. Ghosh S, Viswanath B, Kooti F, Sharma NK, Korlam G, et al. (2012) Understanding and combating link farming in the twitter social network. In: Proceedings of the 21st International Conference on World Wide Web. pp. 61-70.
2. Suh B, Hong L, Pirolli P, Chi EH (2010) Want to be retweeted? large scale analytics on factors impacting retweet in twitter network. In: Social Computing (SocialCom), 2010 IEEE Second International Conference on. pp. 177-184.
3. Cha M, Haddadi H, Benevenuto F, Gummadi KP (2010) Measuring user influence in twitter: The million follower fallacy. In: 4th International AAAI Conference on Weblogs and Social Media. pp. 10-17.
4. Weng J, Lim EP, Jiang J, He Q (2010) Twitterrank: finding topic-sensitive influential twitterers. In: Proceedings of the Third ACM International Conference on Web Search and Data Mining. pp. 261-270.
5. Leavitt A, Burchard E, Fisher D, Gilbert S (2010). The influentials: new approaches for analyzing influence on twitter. In Web Ecology Project, http://www.webecologyproject.org/.
6. Kwak H, Lee C, Park H, Moon S (2010) What is twitter, a social network or a news media? In: Proceedings of the 19th International Conference on World Wide Web. ACM, pp. 591-600.
7. Bakshy E, Hofman JM, Mason WA, Watts DJ (2011) Everyone's an influencer: quantifying influence on twitter. In: Proceedings of the Fourth ACM International Conference on Web Search and Data Mining. pp. 65-74.
8. Saito K, Masuda N (2013) Two types of Twitter users with equally many followers. In: In: Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining. pp. 1425-1426.
9. Java A, Song X, Finin T, Tseng B (2007) Why we twitter: understanding microblogging usage and communities. In: Proceedings of the 9th WebKDD and 1st SNA-KDD 2007 Workshop on Web Mining and Social Network Analysis. pp. 56-65.
10. Takhteyev Y, Gruzd A, Wellman B (2012) Geography of twitter networks. Soc Netw 34: 73-81.
11. Russell M (2011) Mining the Social Web: Analyzing Data from Facebook, Twitter, LinkedIn, and Other Social Media Sites. O'Reilly Media.
12. Welch MJ, Schonfeld U, He D, Cho J (2011) Topical semantics of Twitter links. In: WSDM'11: Proceedings of the Fourth ACM International Conference on Web Search and Data Mining. pp. 327-336.
13. Hopcroft J, Lou T, Tang J (2011) Who will follow you back?: Reciprocal relationship prediction. In: CIKM'11: Proceedings of the 20th ACM International Conference on Information and Knowledge Management. pp. 1137-1146.
14. Tufféry S (2011) Data Mining and Statistics for Decision Making (2nd edition). Chichester: Willey.
15. Newman MEJ (2003) The structure and function of complex networks. SIAM Rev 45: 167-256.
16. Newman MEJ (2010) Networks - An Introduction. Oxford: Oxford University Press.
17. Romero DM, Kleinberg J (2010) The directed closure process in hybrid social-information networks, with an analysis of link formation on Twitter. Proceedings of the Fourth International AAAI Conference on Weblogs and Social Media : 138-145.
18. Brin S, Page L (1998) Anatomy of a large-scale hypertextual web search engine. Proceedings of the Seventh International World Wide Web Conference : 107-117.
19. Langville AN, Meyer CD (2006) Google's PageRank and beyond. Princeton: Princeton University Press.
20. Chang Y, Wang X, Mei Q, Liu Y (2013) Towards Twitter context summarization with user influence models. In: WSDM'13: Proceedings of the sixth ACM international conference on Web search and data mining. pp. 527-536.
21. Fortunato S, Boguñá M, Flammini A, Menczer F (2008) Approximating PageRank from in-degree. Lecture Notes in Computer Science 4936: 59-71.
22. Ghoshal G, Barabási AL (2011) Ranking stability and super-stable nodes in complex networks. Nat Commun 2: 394.
23. Donato D, Laura L, Leonardi S, Millozzi S (2004) Large scale properties of the Webgraph. Eur Phys J B 38: 239-243.
24. Masuda N, Ohtsuki H (2009) Evolutionary dynamics and fixation probabilities in directed networks. New J Phys 11: 033012. Technology