The Dynamics of Health Sentiments with Competitive Interactions in Social Media
Saike He1; Xiaolong Zheng1; Daniel Zeng1,2
2017-08-18
会议名称IEEE Intelligence and Security Informatics 2017 Conference (ISI 2017)
会议录名称Intelligence and Security Informatics (ISI), 2017 IEEE International Conference on
会议日期22-24 July 2017
会议地点Beijing, China
摘要Public sentiments affecting health outcomes are increasingly modulated by social media. Existing literature mainly focus on investigating how network structure affects the contagion of health sentiments. However, most of these studies neglect that the interaction topology change in time. In fact, the change of inter-individual connections over time is associated with individual attributes. The mechanism through which individual attributes reshapes the connection topology is mainly governed by the competition between two principles, i.e., homophily (establishing or reinforcing social connections) and homeostasis (preserving the total strength of social connections to each individual). No existing approaches are yet able to accommodate these two competing effects at the same time. We thus propose a new statistical model (H2 model, Homophily and Homestasis model) to depict the evolution of temporal network, which is governed by the competition of homophily and homeostasis. In addition, we consider the mediation effect of external shock events, which enables us to separate exogenous confounding factors. Evaluation on Twitter data suggests that H2 model can capture long-range sentiment dynamics and external shock events. In sentiment prediction, H2 consistently outperforms existing methods in terms of error rate. Through the model's shock tensor, we successfully detect several typical events, and reveal that users in negative emotions are more influenced by external shock events than those with positive emotions. Our findings have practical significance for those who supervise and guide health sentiments in online communities.
关键词Health Sentiment Competitive Interactions Homophily Homeostasis Social Media
DOI10.1109/ISI.2017.8004882
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文献类型会议论文
条目标识符http://ir.ia.ac.cn/handle/173211/15358
专题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
通讯作者Xiaolong Zheng
作者单位1.1The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
2.2University of Chinese Academy of Sciences, Beijing, China
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Saike He,Xiaolong Zheng,Daniel Zeng. The Dynamics of Health Sentiments with Competitive Interactions in Social Media[C],2017.
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