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

查看全文 作　　者：Wang [1]Qiyao;Li [2]Zhengmin;Jin [1]Yuehui;Cheng [1]Shiduan;Yang [3]Tan 机构地区：[1]State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China;[2]National Computer Network Emergency Response Technical Team/Coordination Center of China, Beijing 100012, China;[3]School of Software Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China 出　　处：《The Journal of China Universities of Posts and Telecommunications》索引2016年第23卷第3期,共8页 基　　金：supported in part by National Key Basic Research and Department (973) Program of China (2013CB329606);Natural Science Foundation of China (61402045) 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. 关 键 词：public sentiment CONFORMITY user-level model emotion prediction social networks