{"title":"Exploring Stock Market Using Twitter Trust Network","authors":"Yefeng Ruan, L. Alfantoukh, A. Durresi","doi":"10.1109/AINA.2015.217","DOIUrl":null,"url":null,"abstract":"As social networks are becoming more and more popular, more and more data are available from them. Researchers are now trying to extract useful information from these big data. One possible usage of social media is to investigate stock market. There are two major events to measure in stock market - price change and trade volume. In this paper, we firstly use our trust framework to build up trust network among Twitter users in a stock market group. We compare trust information extracted from Twitter group with Dow Jones Industrial Average (DJIA) get from Yahoo! Finance. Our results show that by taking trust information into account, they are more correlated than just counting the number of tweets. Also it shows us that trade volume is stronger correlated than price change.","PeriodicalId":6845,"journal":{"name":"2015 IEEE 29th International Conference on Advanced Information Networking and Applications Workshops","volume":"1 1","pages":"428-433"},"PeriodicalIF":0.0000,"publicationDate":"2015-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"25","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE 29th International Conference on Advanced Information Networking and Applications Workshops","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AINA.2015.217","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 25
Abstract
As social networks are becoming more and more popular, more and more data are available from them. Researchers are now trying to extract useful information from these big data. One possible usage of social media is to investigate stock market. There are two major events to measure in stock market - price change and trade volume. In this paper, we firstly use our trust framework to build up trust network among Twitter users in a stock market group. We compare trust information extracted from Twitter group with Dow Jones Industrial Average (DJIA) get from Yahoo! Finance. Our results show that by taking trust information into account, they are more correlated than just counting the number of tweets. Also it shows us that trade volume is stronger correlated than price change.