Thomas Marcoux, Oluwaseyi Adeliyi, Dr Nidhi Agarwal
{"title":"Characterizing video-based online information environment using VTracker","authors":"Thomas Marcoux, Oluwaseyi Adeliyi, Dr Nidhi Agarwal","doi":"10.1145/3487351.3489480","DOIUrl":null,"url":null,"abstract":"YouTube is the second most popular website on the internet and a major actor in information propagation, therefore making it efficient as a potential vehicle of misinformation. Current tools available for video platforms tend to hyperfocus on metadata aggregation and neglect the analysis of the actual videos. In an attempt to provide analysts the tools they need to perform various research (behavioral, political analysis, sociology,etc.), we present VTracker (formerly YouTubeTracker), an online analytical tool. Some of the insight analysts can derive from this tool are inorganic behavior detection and algorithmic manipulation. We aim to make the analysis of YouTube content and user behavior accessible not only to information scientists but also communication researchers, journalists, sociologists, and many more. We demonstrate the utility of the tool through some real world data samples.","PeriodicalId":320904,"journal":{"name":"Proceedings of the 2021 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2021 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3487351.3489480","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
YouTube is the second most popular website on the internet and a major actor in information propagation, therefore making it efficient as a potential vehicle of misinformation. Current tools available for video platforms tend to hyperfocus on metadata aggregation and neglect the analysis of the actual videos. In an attempt to provide analysts the tools they need to perform various research (behavioral, political analysis, sociology,etc.), we present VTracker (formerly YouTubeTracker), an online analytical tool. Some of the insight analysts can derive from this tool are inorganic behavior detection and algorithmic manipulation. We aim to make the analysis of YouTube content and user behavior accessible not only to information scientists but also communication researchers, journalists, sociologists, and many more. We demonstrate the utility of the tool through some real world data samples.