Social media and capital markets: an interdisciplinary bibliometric analysis

Abstract Social media platforms collect information from complex human social behaviors. It has been shown that they significantly impact capital markets. This article conducts a bibliometric analysis of 363 high-quality articles from the Web of Science on social media and capital markets. First, a descriptive analysis was performed, including discipline distribution, growth trends, institutions, publication sources, influential authors, articles, and countries. Second, collaborative networks identify cooperation between countries and institutions in the network analysis section. Bibliometric coupling analysis determines the relationship between journals of different disciplines. Cluster analysis and keyword co-occurrence networks identify hot research topics. Burst detection and keyword time zone analysis track field development. Finally, keyword analysis and clustering analysis are conducted on the research of different disciplines. These sample papers mainly include seven hot topics, including sentiment analysis and financial market prediction. Articles in business and finance focus more on social media’s impact on capital markets. In contrast, information technology articles focus more on extracting information from social media. Each field also has its unique research directions. This paper contributes to a comprehensive understanding of the research on social media and capital markets. It offers perspectives on disciplinary differences, serving as a valuable scholarly reference for conducting in-depth research.

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Publication Details

Journal
Financial Innovation
Published
2025-02-07
DOI
https://doi.org/10.1186/s40854-024-00731-2
Citations
6
Primary Topic
Digital Marketing and Social Media
Type
article
Field-Weighted Citation Impact
25.21

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article

Social media and capital markets: an interdisciplinary bibliometric analysis

Wen Long, Mainzhao Guo
6 citations
Financial Innovation
Digital Marketing and Social Media
25.21
article

Social media and capital markets: an interdisciplinary bibliometric analysis

Wen Long, Mainzhao Guo
article en
6 citations

Abstract

Abstract Social media platforms collect information from complex human social behaviors. It has been shown that they significantly impact capital markets. This article conducts a bibliometric analysis of 363 high-quality articles from the Web of Science on social media and capital markets. First, a descriptive analysis was performed, including discipline distribution, growth trends, institutions, publication sources, influential authors, articles, and countries. Second, collaborative networks identify cooperation between countries and institutions in the network analysis section. Bibliometric coupling analysis determines the relationship between journals of different disciplines. Cluster analysis and keyword co-occurrence networks identify hot research topics. Burst detection and keyword time zone analysis track field development. Finally, keyword analysis and clustering analysis are conducted on the research of different disciplines. These sample papers mainly include seven hot topics, including sentiment analysis and financial market prediction. Articles in business and finance focus more on social media’s impact on capital markets. In contrast, information technology articles focus more on extracting information from social media. Each field also has its unique research directions. This paper contributes to a comprehensive understanding of the research on social media and capital markets. It offers perspectives on disciplinary differences, serving as a valuable scholarly reference for conducting in-depth research.

Financial InnovationVol. 11(1)
Beijing Institute of Big Data Research (CN), University of Chinese Academy of Sciences (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 1%
Digital Marketing and Social Media
25.21
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Social media and capital markets: an interdisciplinary bibliometric analysis — Wen Long, Mainzhao Guo · Financial Innovation (2025) | TGRS Research Map | TGRS