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Volumn , Issue , 2014, Pages 357-360

Inferring user interests in the twitter social network

Author keywords

Labeled LDA; Lists; Twitter; User interests

Indexed keywords

LABELED LDA; LISTS; SOCIAL ANNOTATIONS; STATE-OF-THE-ART TECHNIQUES; TRADITIONAL TECHNIQUES; TWITTER; TWITTER SOCIAL NETWORKS; USER INTERESTS;

EID: 84908885727     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2645710.2645765     Document Type: Conference Paper
Times cited : (114)

References (11)
  • 1
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    • Twitter help center: how to use Twitter lists
    • Twitter help center: how to use Twitter lists. http://bit.ly/how-To-use-Twitter-lists.
  • 2
    • 84979555372 scopus 로고    scopus 로고
    • Short and tweet: Experiments on recommending content from information streams
    • J. Chen, R. Nairn, L. Nelson, M. Bernstein, and E. H. Chi. Short and tweet: experiments on recommending content from information streams. In ACM SIGCHI, 2010.
    • (2010) ACM SIGCHI
    • Chen, J.1    Nairn, R.2    Nelson, L.3    Bernstein, M.4    Chi, E.H.5
  • 3
    • 84871061502 scopus 로고    scopus 로고
    • What is happening right now ⋯ that interests me?: Online topic discovery and recommendation in twitter
    • E. Diaz-Aviles et al. What is Happening Right Now ⋯ That Interests Me?: Online Topic Discovery and Recommendation in Twitter. In ACM CIKM, 2012.
    • (2012) ACM CIKM
    • Diaz-Aviles, E.1
  • 5
    • 84908892234 scopus 로고    scopus 로고
    • Co-factorization machines: Modeling user interests and predicting individual decisions in twitter
    • L. Hong, A. S. Doumith, and B. D. Davison. Co-factorization Machines: Modeling User Interests and Predicting Individual Decisions in Twitter. In ACM WSDM, 2013.
    • (2013) ACM WSDM
    • Hong, L.1    Doumith, A.S.2    Davison, B.D.3
  • 6
    • 84863177076 scopus 로고    scopus 로고
    • Twitobi: A recommendation system for twitter using probabilistic modeling
    • Y. Kim and K. Shim. TWITOBI: A Recommendation System for Twitter Using Probabilistic Modeling. In IEEE ICDM, 2011.
    • (2011) IEEE ICDM
    • Kim, Y.1    Shim, K.2
  • 8
    • 84908866146 scopus 로고    scopus 로고
    • Of pins and tweets: Investigating how users behave across image-And text-based social networks
    • R. Ottoni et al. Of Pins and Tweets: Investigating how users behave across image-And text-based social networks. In AAAI ICWSM, 2014.
    • (2014) AAAI ICWSM
    • Ottoni, R.1
  • 9
    • 80053392186 scopus 로고    scopus 로고
    • Labeled lda: A supervised topic model for credit attribution in multi-labeled corpora
    • D. Ramage, D. Hall, R. Nallapati, and C. D. Manning. Labeled LDA: A Supervised Topic Model for Credit Attribution in Multi-labeled Corpora. In EMNLP, 2009.
    • (2009) EMNLP
    • Ramage, D.1    Hall, D.2    Nallapati, R.3    Manning, C.D.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.