Characterizing Emotion Entrainment in Social Media
He, Saike1; Zheng, Xiaolong1; Bao, Xiuguo2; Ma, Hongyuan2; Zeng, Daniel1,3; Xu, Bo4; Li, Changliang4; Hao, Hongwei4
2014-08-17
Conference NameThe 2014 IEEE/ACM International Conference on Advances in Social Network Analysis and Mining (ASONAM)
Source Publication2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)
Conference Date2014-8-17 ~ 2014-8-20
Conference PlaceBeijing, China
AbstractThe sociological theory of entrainment accounts for the synchronization of human rhythmic modalities through social interactions: they coordinate in a variety of dimensions including linguistic styles, facial expressions, music pace, applause, and so on. Though highly relevant, emotion entrainment has received little attention to date. In addition, most previous studies on entrainment are done through small scale or controlled laboratory studies. In this paper, we investigate emotion entrainment in the context of online social media. To the best of our knowledge, this is the first time that emotion entrainment has been examined on a large scale, real world setting. For this purpose, we propose a framework that can model entrainment phenomenon and measure its effect. Our framework differentiates from previous research by its model-free essential and discerning in entrainment directions. These traits enable us to model entrainment dynamics under few assumptions, and distinguish emotion flow of entrainment. In our studies, we investigate entrainment patterns under different emotion states, i.e. positive, neutral and negative. We discover that entrainments under different emotions all follow a power law distribution. Besides, people are willing to entrain to others under positive emotion, and users with positive emotion are more likely to be entrained. By inspecting the interactions between entrainment and emotion, we reveal that entrainment has an effect of negotiating different emotion types toward an even distribution.
KeywordEmotion Entrainment Transfer Entropy Social Media
DOI10.1109/ASONAM.2014.6921653
URL查看原文
Indexed ByEI
Language英语
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Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/10779
Collection复杂系统管理与控制国家重点实验室_互联网大数据与信息安全
Corresponding AuthorBao, Xiuguo
Affiliation1.The 2014 IEEE/ACM International Conference on Advances in Social Network Analysis and Mining
2.CNCERT/CC
3.Department of Management Information Systems, University of Arizona
4.Institute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
He, Saike,Zheng, Xiaolong,Bao, Xiuguo,et al. Characterizing Emotion Entrainment in Social Media[C],2014.
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