Title :
Exploring Stock Market Using Twitter Trust Network
Author :
Yefeng Ruan ; Alfantoukh, Lina ; Durresi, Arjan
Author_Institution :
Indiana Univ. Purdue Univ. at Indianapolis, Indianapolis, IN, USA
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.
Keywords :
Big Data; information retrieval; social networking (online); stock markets; Dow Jones Industrial Average; Twitter trust network; Yahoo!Finance; big data; price change; social networks; stock market group; trade volume; trust information extraction; Correlation; Fluctuations; Mathematical model; Mood; Sentiment analysis; Stock markets; Twitter;
Conference_Titel :
Advanced Information Networking and Applications (AINA), 2015 IEEE 29th International Conference on
Conference_Location :
Gwangiu
Print_ISBN :
978-1-4799-7904-2
DOI :
10.1109/AINA.2015.217