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Stock trend prediction using sentiment analysis.

Authors :: Xiao Q
Ihnaini B
Source :: PeerJ. Computer science [PeerJ Comput Sci] 2023 Mar 20; Vol. 9, pp. e1293. Date of Electronic Publication: 2023 Mar 20 (Print Publication: 2023).
Publication Year :: 2023
Abstract: These days, the vast amount of data generated on the Internet is a new treasure trove for investors. They can utilize text mining and sentiment analysis techniques to reflect investors' confidence in specific stocks in order to make the most accurate decision. Most previous research just sums up the text sentiment score on each natural day and uses such aggregated score to predict various stock trends. However, the natural day aggregated score may not be useful in predicting different stock trends. Therefore, in this research, we designed two different time divisions: 0:00 <subscript>t</subscript> ∼0:00 <subscript>t+1</subscript> and 9:30 <subscript>t</subscript> ∼9:30 <subscript>t+1</subscript> to study how tweets and news from the different periods can predict the next-day stock trend. 260,000 tweets and 6,000 news from Service stocks (Amazon, Netflix) and Technology stocks (Apple, Microsoft) were selected to conduct the research. The experimental result shows that opening hours division (9:30 <subscript>t</subscript> ∼9:30 <subscript>t+1</subscript> ) outperformed natural hours division (0:00 <subscript>t</subscript> ∼0:00 <subscript>t+1</subscript> ).<br />Competing Interests: The authors declare there are no competing interests.<br /> (©2023 Xiao et al.)