Mehran Kamkarhaghighi, Iuliia Chepurna, S. Aghababaei, M. Makrehchi
{"title":"Discovering Credible Twitter Users in Stock Market Domain","authors":"Mehran Kamkarhaghighi, Iuliia Chepurna, S. Aghababaei, M. Makrehchi","doi":"10.1109/WI.2016.0020","DOIUrl":null,"url":null,"abstract":"Despite extensive research efforts in stock market predictions using social media networks, there still exists a lack of credible sources of information in such media. This study presents a novel approach to measure the credibility of Twitter users in a domain of interest, namely the stock market. This study suggests a correlation between each user's credibility and the extracted features from each follower network: number of followers, number of stock market-related followers, extracted by a $Cashtag-based approach, ratio of stock market-related followers to the total number of followers, and the number of seed user tweets. The results support the initial hypothesis of this study.","PeriodicalId":6513,"journal":{"name":"2016 IEEE/WIC/ACM International Conference on Web Intelligence (WI)","volume":"13 1","pages":"66-72"},"PeriodicalIF":0.0000,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE/WIC/ACM International Conference on Web Intelligence (WI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WI.2016.0020","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
Despite extensive research efforts in stock market predictions using social media networks, there still exists a lack of credible sources of information in such media. This study presents a novel approach to measure the credibility of Twitter users in a domain of interest, namely the stock market. This study suggests a correlation between each user's credibility and the extracted features from each follower network: number of followers, number of stock market-related followers, extracted by a $Cashtag-based approach, ratio of stock market-related followers to the total number of followers, and the number of seed user tweets. The results support the initial hypothesis of this study.