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摘要
This paper proposes a new approach to predict the popularity of content in the Chinese microblogging website Sina Weibo. There are four operations in Sina Weibo, including post, repost-only, repost-and-comment, and comment-only. We model these operations as a bipartite graph, which takes the temporal factor into account by assigning edge weight as an exponential decay function. We then propose a regularization framework on this model to predict the original post's future popularity. Experimental results show that our method outperforms other methods in predicting the post's future popularity, especially for short-term prediction.
- 出版日期2016-12
- 单位北京交通大学
