[Purpose/significance] Microblog retweeting is the key way for information diffusion. The study of user retweeting behavior can better understand the information diffusion mechanism in microblog, which is of great significance for hot topic detection, public opinion monitoring and microblog marketing and so on. In this paper, we analyze the factors that affect users' retweeting behavior. The users' interest isn't comprehensive and accurate, and the influence of emotional divergence on users' is not considered in the previous research. Thus, we propose a microblog retweeting prediction model integrating emotional divergence and user interests.[Method/process] Firstly, we built a Wikipedia knowledge base by extracting semantic relations from Wikipedia, and extended the semantic feature of microblog text vector by using the Wikipedia knowledge base, which could solve the semantic sparse problem. To extract users' interest themes and their influence on users, we clustered the users' microblogs which was extended by Wikipedia knowledge base. Secondly, we calculated the emotional intensity of all kinds of emotions in microblog, extracting the emotional divergence features. Finally, combining users' behavior features, users' interaction features, microblog features, users' interests features and emotional divergence features, we used SVM to achieve the prediction of microblog retweeting.[Result/conclusion]The experimental results show that the proposed method can effectively improve the performance of microblog retweeting prediction.
Tang Xiaobo
,
Luo Yingli
. Integrating Emotional Divergence and User Interests into the Prediction of Microblog Retweeting[J]. Library and Information Service, 2017
, 61(9)
: 102
-110
.
DOI: 10.13266/j.issn.0252-3116.2017.09.013
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