Sentiment analysis for stock market research: A bibliometric study

Abstract

Sentiment analysis is widely utilized in stock market research. To comprehensively review the field, a bibliometric analysis was performed on 223 articles relating to sentiment analysis for stock markets from 2010 to 2022 collected from Web of Science database. Specifically, we recognized active affiliations, countries/regions, publication sources, and subject areas, identified top cited research articles, visualized scientific collaborations among authors, affiliations, and countries/regions, and revealed main research topics. Findings indicate that computer science journals are active in publishing works on sentiment analysis-facilitated stock market research. The research on sentiment analysis-facilitated stock market has attracted researchers from a wide geographic distribution, who have made significant contributions. The intensity of intra-regional collaborations is higher than that of inter-regional collaborations. Thematic topics regarding stock market research using sentiment analysis were detected using keyword mapping, with the following research topics being widely concerned by scholars: deep learning for stock market prediction, financial news sentiment empowered stock trend forecasting, effects of investor sentiment on financial market, and microblog sentiment classification for market prediction. Findings are helpful in depicting research status to researchers and practitioners, raising their awareness of research frontiers when planning research projects concerning sentiment analysis’s application in stock markets.

Keywords

• Sentiment analysis
• Stock market
• Bibliometric analysis
• Scientific collaborations
• Keyword mapping
• Research topics