Analyzing and predicting viral tweets-Reference-Cited by-同舟云学术

Analyzing and predicting viral tweets

Published:2013 Issue: Volume: Page:
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Container-title:Proceedings of the 22nd International Conference on World Wide Web - WWW '13 Companion
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Author:

Jenders Maximilian¹,Kasneci Gjergji¹,Naumann Felix¹

Affiliation:

1. Hasso Plattner Institute, Potsdam, Germany

Publisher

ACM Press

Reference18 articles.

1. P. André, M. S. Bernstein, and K. Luther. Who Gives A Tweet? Evaluating Microblog Content Value. In Proceedings of the 16th ACM Conference on Computer Supported Cooperative Work and Social Computing, CSCW, pages 471--474, 2012.

2. E. Bakshy, J. M. Hofman, D. J. Watts, and W. A. Mason. Everyone's an Influencer: Quantifying Influence on Twitter. In Proceedings of the 4th ACM International Conference on Web Search and Data Mining, WSDM, pages 65--74, 2011.

3. J. Bollen, A. Pepe, and H. Mao. Modeling Public Mood and Emotion: Twitter Sentiment and Socio-economic Phenomena. In Proceedings of the Fifth International AAAI Conference on Weblogs and Social Media, ICWSM, pages 450--453, 2011.

4. D. Boyd, S. Golder, and G. Lotan. Tweet, Tweet, Retweet: Conversational Aspects of Retweeting on Twitter. In Proceedings of the 43rd Hawaii International Conference on System Sciences, number 6 in HICSS, pages 1--10, 2010.

5. M. Cha and K. P. Gummadi. Measuring User Influence in Twitter: The Million Follower Fallacy. In Proceedings of the 4th International AAAI Conference on Weblogs and Social Media, ICWSM, 2010.

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