Predicting News Popularity by Mining Online Discussions-Reference-Cited by-同舟云学术

Predicting News Popularity by Mining Online Discussions

Published:2016 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 25th International Conference Companion on World Wide Web - WWW '16 Companion
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Author:

Rizos Georgios¹,Papadopoulos Symeon¹,Kompatsiaris Yiannis¹

Affiliation:

1. CERTH-ITI, Thessaloniki, Greece

Funder

European Commission

Publisher

ACM Press

Reference16 articles.

1. S. Bora, H. Singh, A. Sen, A. Bagchi, and P. Singla. On the role of conductance, geography and topology in predicting hashtag virality. arXiv preprint arXiv:1504.05351, 2015.

2. L. Breiman. Random forests. Machine learning, 45(1):5--32, 2001.

3. J. Cheng, L. Adamic, P. A. Dow, J. M. Kleinberg, and J. Leskovec. Can cascades be predicted? In Proceedings of the 23rd international conference on World Wide Web, pages 925--936, 2014.

4. K. Garimella, G. D. F. Morales, A. Gionis, and M. Mathioudakis. Quantifying controversy in social media. arXiv preprint arXiv:1507.05224, 2015.

5. S. Goel, A. Anderson, J. Hofman, and D. Watts. The structural virality of online diffusion. Preprint, 22:26, 2013.

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