{"title":"Impact Of Emotions on Information Seeking And Sharing Behaviors During Pandemic","authors":"Smitha Muthya Sudheendra, Hao Xu, Jisu Huh, Jaideep Srivastava","doi":"arxiv-2409.10754","DOIUrl":null,"url":null,"abstract":"We propose a novel approach to assess the public's coping behavior during the\nCOVID-19 outbreak by examining the emotions. Specifically, we explore (1)\nchanges in the public's emotions with the COVID-19 crisis progression and (2)\nthe impacts of the public's emotions on their information-seeking,\ninformation-sharing behaviors, and compliance with stay-at-home policies. We\nbase the study on the appraisal tendency framework, detect the public's\nemotions by fine-tuning a pre-trained RoBERTa model, and cross-analyze\nthird-party behavioral data. We demonstrate the feasibility and reliability of\nour proposed approach in providing a large-scale examination of the publi's\nemotions and coping behaviors in a real-world crisis: COVID-19. The approach\ncomplements prior crisis communication research, mainly based on self-reported,\nsmall-scale experiments and survey data. Our results show that anger and fear\nare more prominent than other emotions experienced by the public at the\npandemic's outbreak stage. Results also show that the extent of low certainty\nand passive emotions (e.g., sadness, fear) was related to increased\ninformation-seeking and information-sharing behaviors. Additionally,\nhigh-certainty (e.g., anger) and low-certainty (e.g., sadness, fear) emotions\nduring the outbreak correlated to the public's compliance with stay-at-home\norders.","PeriodicalId":501032,"journal":{"name":"arXiv - CS - Social and Information Networks","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - CS - Social and Information Networks","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.10754","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
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.