{"title":"是什么让辟谣在社交媒体上走红?","authors":"Anjan Pal, Snehasish Banerjee, Avneet Kaur","doi":"10.1109/IMCOM56909.2023.10035545","DOIUrl":null,"url":null,"abstract":"This paper investigates the relationship between the characteristics of online rumor rebuttals and their virality on social media. Virality was conceptualized in terms of the volume of Likes (affective evaluation), Comments (message deliberation), and Shares (viral reach) attracted by rumor rebuttals on Facebook. The dataset included 479 online rumor rebuttal posts. Qualitative content analysis was employed to identify characteristics of the rebuttals while quantitative methods were used to examine how these characteristics predicted their virality. Rebuttal virality was found to be positively predicted by message posters' credibility (#Likes, #Comments, and #Shares), justification of the rebuttal (#Likes and #Comments), call to action (#Comments and #Shares), and the presence of images (#Comments). In contrast, rebuttal virality was negatively predicted by the presence of debunking statements (#Comments) and URLs (#Likes, #Comments).","PeriodicalId":230213,"journal":{"name":"2023 17th International Conference on Ubiquitous Information Management and Communication (IMCOM)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"What Makes Rumor Rebuttals Viral on Social Media?\",\"authors\":\"Anjan Pal, Snehasish Banerjee, Avneet Kaur\",\"doi\":\"10.1109/IMCOM56909.2023.10035545\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper investigates the relationship between the characteristics of online rumor rebuttals and their virality on social media. Virality was conceptualized in terms of the volume of Likes (affective evaluation), Comments (message deliberation), and Shares (viral reach) attracted by rumor rebuttals on Facebook. The dataset included 479 online rumor rebuttal posts. Qualitative content analysis was employed to identify characteristics of the rebuttals while quantitative methods were used to examine how these characteristics predicted their virality. Rebuttal virality was found to be positively predicted by message posters' credibility (#Likes, #Comments, and #Shares), justification of the rebuttal (#Likes and #Comments), call to action (#Comments and #Shares), and the presence of images (#Comments). In contrast, rebuttal virality was negatively predicted by the presence of debunking statements (#Comments) and URLs (#Likes, #Comments).\",\"PeriodicalId\":230213,\"journal\":{\"name\":\"2023 17th International Conference on Ubiquitous Information Management and Communication (IMCOM)\",\"volume\":\"47 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-01-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 17th International Conference on Ubiquitous Information Management and Communication (IMCOM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IMCOM56909.2023.10035545\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 17th International Conference on Ubiquitous Information Management and Communication (IMCOM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IMCOM56909.2023.10035545","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper investigates the relationship between the characteristics of online rumor rebuttals and their virality on social media. Virality was conceptualized in terms of the volume of Likes (affective evaluation), Comments (message deliberation), and Shares (viral reach) attracted by rumor rebuttals on Facebook. The dataset included 479 online rumor rebuttal posts. Qualitative content analysis was employed to identify characteristics of the rebuttals while quantitative methods were used to examine how these characteristics predicted their virality. Rebuttal virality was found to be positively predicted by message posters' credibility (#Likes, #Comments, and #Shares), justification of the rebuttal (#Likes and #Comments), call to action (#Comments and #Shares), and the presence of images (#Comments). In contrast, rebuttal virality was negatively predicted by the presence of debunking statements (#Comments) and URLs (#Likes, #Comments).
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