Finding interesting posts in Twitter based on retweet graph analysis

SIGIR'12 - Proceedings of the International ACM SIGIR Conference on Research and Development in Information Retrieval

Volumn , Issue , 2012, Pages 1073-1074

  Yang, Min Chul ^a   Lee, Jung Tae ^a   Lee, Seung Wook ^a   Rim, Hae Chang ^a  

^a Korea University   (South Korea)

Author keywords

hits; social network; tweet ranking; Twitter

Indexed keywords

BASELINE METHODS; GRAPH ANALYSIS; HITS; HITS ALGORITHMS; NETWORKING SERVICES; REAL WORLD DATA; SOCIAL NETWORKS; STATIC RANKINGS; TWEET RANKING; TWITTER;

ALGORITHMS; INFORMATION RETRIEVAL;

SOCIAL NETWORKING (ONLINE);

EID: 84866603413     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2348283.2348475     Document Type: Conference Paper

References (4)

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3. L. Hong, O. Dan, and B. D. Davison. Predicting popular messages in twitter. In WWW, 2011.
4. J. M. Kleinberg. Authoritative sources in a hyperlinked environment. J. ACM, 46(5), 1999.