Exploring Entrainment Patterns of Human Emotion in Social Media
He, Saike1; Zheng, Xiaolong1; Zeng, Daniel1,2; Luo, Chuan1; Zhang, Zhu1
Source PublicationPLOS ONE
2016-03-08
Volume11Issue:3Pages:e0150630
SubtypeArticle
AbstractEmotion entrainment, which is generally defined as the synchronous convergence of human emotions, performs many important social functions. However, what the specific mechanisms of emotion entrainment are beyond in-person interactions, and how human emotions evolve under different entrainment patterns in large-scale social communities, are still unknown. In this paper, we aim to examine the massive emotion entrainment patterns and understand the underlying mechanisms in the context of social media. As modeling emotion dynamics on a large scale is often challenging, we elaborate a pragmatic framework to characterize and quantify the entrainment phenomenon. By applying this framework on the datasets from two large-scale social media platforms, we find that the emotions of online users entrain through social networks. We further uncover that online users often form their relations via dual entrainment, while maintain it through single entrainment. Remarkably, the emotions of online users are more convergent in nonreciprocal entrainment. Building on these findings, we develop an entrainment augmented model for emotion prediction. Experimental results suggest that entrainment patterns inform emotion proximity in dyads, and encoding their associations promotes emotion prediction. This work can further help us to understand the underlying dynamic process of large-scale online interactions and make more reasonable decisions regarding emergency situations, epidemic diseases, and political campaigns in cyberspace.
WOS HeadingsScience & Technology
DOI10.1371/journal.pone.0150630
URL查看原文
Indexed BySCI ; SSCI
Language英语
Funding OrganizationNational Natural Science Foundation of China(71402177 ; National Institutes of Health (NIH) of the United States of America(1R01DA037378-01) ; Ministry of Health(2013ZX10004218 ; National Institutes of Health (NIH) of USA(1R01DA037378-01) ; 71472175 ; 2012ZX10004801) ; 71025001 ; 61175040 ; 71103180)
WOS Research AreaScience & Technology - Other Topics
WOS SubjectMultidisciplinary Sciences
WOS IDWOS:000371991300037
Citation statistics
Cited Times:9[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/10772
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 AuthorZheng, Xiaolong
Affiliation1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
2.Univ Arizona, Dept Management Informat Syst, Tucson, AZ 85721 USA
Recommended Citation
GB/T 7714
He, Saike,Zheng, Xiaolong,Zeng, Daniel,et al. Exploring Entrainment Patterns of Human Emotion in Social Media[J]. PLOS ONE,2016,11(3):e0150630.
APA He, Saike,Zheng, Xiaolong,Zeng, Daniel,Luo, Chuan,&Zhang, Zhu.(2016).Exploring Entrainment Patterns of Human Emotion in Social Media.PLOS ONE,11(3),e0150630.
MLA He, Saike,et al."Exploring Entrainment Patterns of Human Emotion in Social Media".PLOS ONE 11.3(2016):e0150630.
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