TY - GEN
T1 - Characterizing emotion entrainment in social media
AU - He, Saike
AU - Zheng, Xiaolong
AU - Bao, Xiuguo
AU - Ma, Hongyuan
AU - Zeng, Daniel
AU - Xu, Bo
AU - Li, Changliang
AU - Hao, Hongwei
PY - 2014/10/10
Y1 - 2014/10/10
N2 - The 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.
AB - The 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.
KW - emotion entrainment
KW - social media
KW - transfer entropy
UR - http://www.scopus.com/inward/record.url?scp=84911145263&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84911145263&partnerID=8YFLogxK
U2 - 10.1109/ASONAM.2014.6921653
DO - 10.1109/ASONAM.2014.6921653
M3 - Conference contribution
AN - SCOPUS:84911145263
T3 - ASONAM 2014 - Proceedings of the 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
SP - 642
EP - 648
BT - ASONAM 2014 - Proceedings of the 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
A2 - Ester, Martin
A2 - Xu, Guandong
A2 - Wu, Xindong
A2 - Wu, Xindong
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2014
Y2 - 17 August 2014 through 20 August 2014
ER -