{"title":"Social Network Analysis of Misinformation Spreading and Science Communication during <scp>COVID</scp>‐19","authors":"Jieli Liu, Ravi Maithrey Regulagedda","doi":"10.1002/pra2.944","DOIUrl":null,"url":null,"abstract":"ABSTRACT The outbreak of COVID‐19 has resulted in an increase in health misinformation spreading on social media, emphasizing the need for effective science communication to combat this issue. This study aimed to analyze the relationship between misinformation spreading and science communication network. We identified misinformation spreaders, scientists, and laypeople from COVID vaccine‐related tweets, and we carried out a network analysis to examine the ingroup and intergroup interactions. We found that individuals in all three groups tended to interact with people who were dissimilar to them. Additionally, we found that the spreading of misinformation and the science communication network are polarized. Finally, suggestions were provided to achieve higher engagement in science communication.","PeriodicalId":37833,"journal":{"name":"Proceedings of the Association for Information Science and Technology","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Association for Information Science and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1002/pra2.944","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Social Sciences","Score":null,"Total":0}
引用次数: 0
Abstract
ABSTRACT The outbreak of COVID‐19 has resulted in an increase in health misinformation spreading on social media, emphasizing the need for effective science communication to combat this issue. This study aimed to analyze the relationship between misinformation spreading and science communication network. We identified misinformation spreaders, scientists, and laypeople from COVID vaccine‐related tweets, and we carried out a network analysis to examine the ingroup and intergroup interactions. We found that individuals in all three groups tended to interact with people who were dissimilar to them. Additionally, we found that the spreading of misinformation and the science communication network are polarized. Finally, suggestions were provided to achieve higher engagement in science communication.
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