User interest and social influence based emotion prediction for individuals

Authors:
Yun Yang;Peng Cui;Wenwu Zhu;Shiqiang Yang
Affiliations:
Beijing Key Laboratory of Networked Multimedia, Tsinghua University, China, Beijing, China;Beijing Key Laboratory of Networked Multimedia, Tsinghua University, China, Beijing, China;Beijing Key Laboratory of Networked Multimedia, Tsinghua University, China, Beijing, China;Beijing Key Laboratory of Networked Multimedia, Tsinghua University, China, Beijing, China
Venue:
Proceedings of the 21st ACM international conference on Multimedia
Year:
2013

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Abstract

Emotions are playing significant roles in daily life, making emotion prediction important. To date, most of state-of-the-art methods make emotion prediction for the masses which are invalid for individuals. In this paper, we propose a novel emotion prediction method for individuals based on user interest and social influence. To balance user interest and social influence, we further propose a simple yet efficient weight learning method in which the weights are obtained from users' behaviors. We perform experiments in real social media network, with 4,257 users and 2,152,037 microblogs. The experimental results demonstrate that our method outperforms traditional methods with significant performance gains.