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ULM： A user-level model for emotion prediction in social networks

ULM: A user-level model for emotion prediction in social networks
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摘要 Users express their emotions in online social networks （OSNs）. Studying emotions is important for understanding user behaviors. Existing methods in emotion prediction mainly use personal emotion and friend emotion to predict target emotion. In this study, public sentiment is introduced to denote the sentiment of the majority in the network. Public conformity is calculated to measure the degree of a user conforming to the public sentiment. According to the public conformity, users are categorized into three classes： Approvers, independents, and starters. A user-level model for emotion prediction is proposed to predict target emotions of different classes of users, taking into account of the public sentiment, individual sentiment, friend sentiment and pseudo-friend sentiment. Relations between the public conformity and the structure of the network are studied. Experiments conducted on Sina Weibo show that the proposed model could achieve performance improvements to some existing methods in most cases. Users express their emotions in online social networks （OSNs）. Studying emotions is important for understanding user behaviors. Existing methods in emotion prediction mainly use personal emotion and friend emotion to predict target emotion. In this study, public sentiment is introduced to denote the sentiment of the majority in the network. Public conformity is calculated to measure the degree of a user conforming to the public sentiment. According to the public conformity, users are categorized into three classes： Approvers, independents, and starters. A user-level model for emotion prediction is proposed to predict target emotions of different classes of users, taking into account of the public sentiment, individual sentiment, friend sentiment and pseudo-friend sentiment. Relations between the public conformity and the structure of the network are studied. Experiments conducted on Sina Weibo show that the proposed model could achieve performance improvements to some existing methods in most cases.
作者 Wang Qiyao Li Zhengmin Jin Yuehui Cheng Shiduan Yang Tan
机构地区 State Key Laboratory of Networking and Switching Technology National Computer Network Emergency Response Technical Team/Coordination Center of China School of Software Engineering
出处 《The Journal of China Universities of Posts and Telecommunications》 EI CSCD 2016年第3期63-69,88,共8页 中国邮电高校学报（英文版）
基金 supported in part by National Key Basic Research and Department (973) Program of China (2013CB329606) Natural Science Foundation of China (61402045)
关键词 public sentiment CONFORMITY user-level model emotion prediction social networks public sentiment, conformity, user-level model, emotion prediction, social networks
分类号 TP393.09 [自动化与计算机技术—计算机应用技术]
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参考文献15

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The Journal of China Universities of Posts and Telecommunications
2016年 第3期

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