Learning sentimental influence in twitter

Proceedings - 2011 International Conference on Future Computer Sciences and Application, ICFCSA 2011

Volumn , Issue , 2011, Pages 119-122

  Wu, Ye ^a,b   Ren, Fuji ^b  

^a BEIJING UNIVERSITY OF POSTS AND TELECOMMUNICATIONS   (China)

^b UNIVERSITY OF TOKUSHIMA   (Japan)

Author keywords

Influence analysis; Sentiment analysis; Twitter

Indexed keywords

DESIGN MODELS; INFLUENCE ANALYSIS; ONLINE DATA; ONLINE SOCIAL NETWORKS; SENTIMENT ANALYSIS; SOCIAL MEDIA; SOCIAL NETWORKS; TWITTER;

COMPUTER APPLICATIONS; COMPUTER SCIENCE; DATA MINING; PROBABILITY;

SOCIAL NETWORKING (ONLINE);

EID: 80052150529     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICFCSA.2011.34     Document Type: Conference Paper

References (10)

1. I. King, J. Li, and K. T. Chan, "A Brief Survey of Computational Approaches in Social Computing," IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks, IEEE Press, 2009.
2. S. Bharathi, D. Kempe, and M. Salek, "Competitive influence maximization in social networks", Lecture Notes in Computer Science, 2007, pp. 306-311.
3. J. Tang, J. Sun, C. Wang, and Zi Yang, "Social influence analysis in large-scale networks," Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining, 2009, pp. 807-816.
4. B. Pang, L. Lee, and S. Vaithyanathan, "Thumbs up? Sentiment classification using machine learning techniques", Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), 2002, pp. 79-86.
5. th Annual Meeting on Association for Computational Linguistics (ACL '02), pp. 417-424.
6. A. Goyal, F. Bonchi, and Laks V. S. Lakshmanan, "Learning influence probabilities in social networks", WSDM '10 Proceedings of the third ACM international conference on Web search and data mining, 2010.
7. J. Weng, E. P. Lim, J. Jiang, and Qi He, "TwitterRank: finding topic-sensitive influential twitterers", WSDM '10 Proceedings of the third ACM international conference on Web search and data mining, 2010.
8. B. O'Connor, R. Balasubramanyan, B. R. Routledge, and N. A. Smith, "From Tweets to Polls: Linking Text Sentiment to Public Opinion Time Series", Proceedings of the International AAAI Conference on Weblogs and Social Media, 2010.
9. T. Wilson, J. Wiebe, and P. Hoffman, "Recognizing contextual polarity in phrase-level sentiment analysis", HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing, 2005.
10. th edition, 1990.