{"title":"将同伴提供的可信度标签作为一种网络误导干预措施","authors":"Saumya Pareek, Jorge Goncalves","doi":"10.1016/j.ijhcs.2024.103276","DOIUrl":null,"url":null,"abstract":"<div><p>Misinformation is rampant on social media, and existing platform-supplied interventions offer limited effectiveness. In this study, we examine the effectiveness of credibility labels that dispute the accuracy of information when they are supplied by one’s peers at different levels of relationship closeness and political agreement. We investigate four variants of these labels using a 2 (<em>strong</em> vs. <em>weak</em> tie strength) x 2 (<em>high</em> vs. <em>low</em> political agreement) between-subjects factorial design. We find that credibility disputes raised by one’s co-partisans (peers with similar political beliefs) significantly reduced belief in misinformation, irrespective of one’s relationship closeness with the peer. Our findings also reveal that in contrast to prior literature, a peer’s knowledgeability may be more potent than trustworthiness in causing belief change, and that trust can sometimes manifest even in the credibility judgement of distant peers, when perceived to have expertise or a fact-checking tendency. We further highlight the dual nature of these credibility labels, discussing scenarios in which disputes by hyper-partisan members of the opposite party can enforce belief in misinformation. We conclude by discussing how peer-supplied credibility disputes can benefit social media, especially echo chambers with high political homophily, where disputes by a co-partisan may be met with less resistance and persuade significantly reduced belief in fake news.</p></div>","PeriodicalId":54955,"journal":{"name":"International Journal of Human-Computer Studies","volume":null,"pages":null},"PeriodicalIF":5.3000,"publicationDate":"2024-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1071581924000600/pdfft?md5=c342a4fad488053cf8d58b2d854e07e4&pid=1-s2.0-S1071581924000600-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Peer-supplied credibility labels as an online misinformation intervention\",\"authors\":\"Saumya Pareek, Jorge Goncalves\",\"doi\":\"10.1016/j.ijhcs.2024.103276\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Misinformation is rampant on social media, and existing platform-supplied interventions offer limited effectiveness. In this study, we examine the effectiveness of credibility labels that dispute the accuracy of information when they are supplied by one’s peers at different levels of relationship closeness and political agreement. We investigate four variants of these labels using a 2 (<em>strong</em> vs. <em>weak</em> tie strength) x 2 (<em>high</em> vs. <em>low</em> political agreement) between-subjects factorial design. We find that credibility disputes raised by one’s co-partisans (peers with similar political beliefs) significantly reduced belief in misinformation, irrespective of one’s relationship closeness with the peer. Our findings also reveal that in contrast to prior literature, a peer’s knowledgeability may be more potent than trustworthiness in causing belief change, and that trust can sometimes manifest even in the credibility judgement of distant peers, when perceived to have expertise or a fact-checking tendency. We further highlight the dual nature of these credibility labels, discussing scenarios in which disputes by hyper-partisan members of the opposite party can enforce belief in misinformation. We conclude by discussing how peer-supplied credibility disputes can benefit social media, especially echo chambers with high political homophily, where disputes by a co-partisan may be met with less resistance and persuade significantly reduced belief in fake news.</p></div>\",\"PeriodicalId\":54955,\"journal\":{\"name\":\"International Journal of Human-Computer Studies\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":5.3000,\"publicationDate\":\"2024-04-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S1071581924000600/pdfft?md5=c342a4fad488053cf8d58b2d854e07e4&pid=1-s2.0-S1071581924000600-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Human-Computer Studies\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1071581924000600\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, CYBERNETICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Human-Computer Studies","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1071581924000600","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, CYBERNETICS","Score":null,"Total":0}
Peer-supplied credibility labels as an online misinformation intervention
Misinformation is rampant on social media, and existing platform-supplied interventions offer limited effectiveness. In this study, we examine the effectiveness of credibility labels that dispute the accuracy of information when they are supplied by one’s peers at different levels of relationship closeness and political agreement. We investigate four variants of these labels using a 2 (strong vs. weak tie strength) x 2 (high vs. low political agreement) between-subjects factorial design. We find that credibility disputes raised by one’s co-partisans (peers with similar political beliefs) significantly reduced belief in misinformation, irrespective of one’s relationship closeness with the peer. Our findings also reveal that in contrast to prior literature, a peer’s knowledgeability may be more potent than trustworthiness in causing belief change, and that trust can sometimes manifest even in the credibility judgement of distant peers, when perceived to have expertise or a fact-checking tendency. We further highlight the dual nature of these credibility labels, discussing scenarios in which disputes by hyper-partisan members of the opposite party can enforce belief in misinformation. We conclude by discussing how peer-supplied credibility disputes can benefit social media, especially echo chambers with high political homophily, where disputes by a co-partisan may be met with less resistance and persuade significantly reduced belief in fake news.
期刊介绍:
The International Journal of Human-Computer Studies publishes original research over the whole spectrum of work relevant to the theory and practice of innovative interactive systems. The journal is inherently interdisciplinary, covering research in computing, artificial intelligence, psychology, linguistics, communication, design, engineering, and social organization, which is relevant to the design, analysis, evaluation and application of innovative interactive systems. Papers at the boundaries of these disciplines are especially welcome, as it is our view that interdisciplinary approaches are needed for producing theoretical insights in this complex area and for effective deployment of innovative technologies in concrete user communities.
Research areas relevant to the journal include, but are not limited to:
• Innovative interaction techniques
• Multimodal interaction
• Speech interaction
• Graphic interaction
• Natural language interaction
• Interaction in mobile and embedded systems
• Interface design and evaluation methodologies
• Design and evaluation of innovative interactive systems
• User interface prototyping and management systems
• Ubiquitous computing
• Wearable computers
• Pervasive computing
• Affective computing
• Empirical studies of user behaviour
• Empirical studies of programming and software engineering
• Computer supported cooperative work
• Computer mediated communication
• Virtual reality
• Mixed and augmented Reality
• Intelligent user interfaces
• Presence
...