{"title":"Conspiracy and Rumor Correction: Analysis of Social Media Users' Comments","authors":"Gilang Maulana Majid, Anjan Pal","doi":"10.1109/ICICT50521.2020.00058","DOIUrl":null,"url":null,"abstract":"This study explores online users' comments in response to rumor corrections. Specifically, it considers a video rumor correction that was posted on YouTube and debunked a rumor in the wake of Indonesia's post-election protests and riots. Content analysis was employed on 500 comments that were posted in response to the rumor-corrections. This study finds that the volume of anti-correction comments (53.60%) was approximately five times greater than the volume of the pro-correction comments (10.80%). In-depth analysis of anti-correction comments revealed different voices, including rejection of evidence, distrust in authorities, critical inspection of evidence, and lack of sufficient evidence. Essentially, this study shows that rumor corrections must be followed-up in order to gain public trust.","PeriodicalId":445000,"journal":{"name":"2020 3rd International Conference on Information and Computer Technologies (ICICT)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 3rd International Conference on Information and Computer Technologies (ICICT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICICT50521.2020.00058","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
This study explores online users' comments in response to rumor corrections. Specifically, it considers a video rumor correction that was posted on YouTube and debunked a rumor in the wake of Indonesia's post-election protests and riots. Content analysis was employed on 500 comments that were posted in response to the rumor-corrections. This study finds that the volume of anti-correction comments (53.60%) was approximately five times greater than the volume of the pro-correction comments (10.80%). In-depth analysis of anti-correction comments revealed different voices, including rejection of evidence, distrust in authorities, critical inspection of evidence, and lack of sufficient evidence. Essentially, this study shows that rumor corrections must be followed-up in order to gain public trust.