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Text Sentiment Mining used for Constructing Investor Sentiment in Social Media: Survey and Recommendations

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  • Qing Liu
  • Hosung Son

Abstract

The measurement of investor sentiment in social media remains a challenging and unresolved issue. The lack of transparency in sentiment tracking tools and survey methodologies in financial research complicates the distinction between measurement noise and genuine online sentiment in historical studies. This review aims to provide structured recommendations for improving the reliability and standardization of investor sentiment measurement in social media. The findings contribute to enhancing the reliability, replicability, and comparability of studies on investor sentiment, offering valuable guidance for future research in this domain.

Suggested Citation

  • Qing Liu & Hosung Son, 2025. "Text Sentiment Mining used for Constructing Investor Sentiment in Social Media: Survey and Recommendations," SAGE Open, , vol. 15(1), pages 21582440251, March.
    • Handle: RePEc:sae:sagope:v:15:y:2025:i:1:p:21582440251328535
    DOI: 10.1177/21582440251328535
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