Collaborative topic regression for predicting topic-based social influence

Author:

Hamzehei AssoORCID,Wong Raymond K.,Koutra Danai,Chen Fang

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Reference34 articles.

1. Barbieri, N., Bonchi, F., & Manco, G. (2012). Topic-aware social influence propagation models. In ICDM (pp. 81–90).

2. Bingol, K., Eravci, B., Etemoglu, C. O., Ferhatosmanoglu, H., & Gedik, B. (2016). Topic-based influence computation in social networks under resource constraints. IEEE Transactions on Services Computing, PP(99), 1–1.

3. Cano, A. E., Mazumdar, S., & Ciravegna, F. (2014). Social influence analysis in microblogging platforms: A topic-sensitive based approach. SWJ, 5(5), 357–372.

4. Cataldi, M., & Aufaure, M. A. (2015). The 10 million follower fallacy: Audience size does not prove domain-influence on twitter. KAIS, 44(3), 559–580.

5. Chen, C., Zheng, X., Wang, Y., Hong, F., & Lin, Z. (2014). Context-aware collaborative topic regression with social matrix factorization for recommender systems. In AAAI.

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