Impact Of Emotions on Information Seeking And Sharing Behaviors During Pandemic

Smitha Muthya Sudheendra, Hao Xu, Jisu Huh, Jaideep Srivastava
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Abstract

We propose a novel approach to assess the public's coping behavior during the COVID-19 outbreak by examining the emotions. Specifically, we explore (1) changes in the public's emotions with the COVID-19 crisis progression and (2) the impacts of the public's emotions on their information-seeking, information-sharing behaviors, and compliance with stay-at-home policies. We base the study on the appraisal tendency framework, detect the public's emotions by fine-tuning a pre-trained RoBERTa model, and cross-analyze third-party behavioral data. We demonstrate the feasibility and reliability of our proposed approach in providing a large-scale examination of the publi's emotions and coping behaviors in a real-world crisis: COVID-19. The approach complements prior crisis communication research, mainly based on self-reported, small-scale experiments and survey data. Our results show that anger and fear are more prominent than other emotions experienced by the public at the pandemic's outbreak stage. Results also show that the extent of low certainty and passive emotions (e.g., sadness, fear) was related to increased information-seeking and information-sharing behaviors. Additionally, high-certainty (e.g., anger) and low-certainty (e.g., sadness, fear) emotions during the outbreak correlated to the public's compliance with stay-at-home orders.
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大流行病期间情绪对信息搜索和共享行为的影响
我们提出了一种新方法,通过研究情绪来评估公众在 COVID-19 爆发期间的应对行为。具体来说,我们探讨了(1)公众情绪随着 COVID-19 危机进展的变化;(2)公众情绪对其信息搜寻、信息共享行为和遵守留守政策的影响。我们的研究基于评价倾向框架,通过微调预先训练好的 RoBERTa 模型来检测公众情绪,并交叉分析第三方行为数据。我们证明了所提出方法的可行性和可靠性,可以对真实世界危机中的公众情绪和应对行为进行大规模检测:COVID-19。该方法补充了之前的危机传播研究,这些研究主要基于自我报告、小规模实验和调查数据。我们的研究结果表明,在疫情爆发阶段,公众的愤怒和恐惧情绪比其他情绪更为突出。结果还显示,低确定性和被动情绪(如悲伤、恐惧)的程度与信息搜寻和信息分享行为的增加有关。此外,疫情爆发期间的高确定性情绪(如愤怒)和低确定性情绪(如悲伤、恐惧)与公众遵守留在家中的命令有关。
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