JOURNAL ARTICLE

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

Qing LiuHosung Son

Year: 2025 Journal:   SAGE Open Vol: 15 (1)   Publisher: SAGE Publishing

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.

Keywords:
Sentiment analysis Social media Psychology Data science Computer science Advertising Natural language processing Business World Wide Web

Metrics

0
Cited By
0.00
FWCI (Field Weighted Citation Impact)
151
Refs
0.03
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Topics

Sentiment Analysis and Opinion Mining
Physical Sciences →  Computer Science →  Artificial Intelligence
Advanced Text Analysis Techniques
Physical Sciences →  Computer Science →  Artificial Intelligence
Topic Modeling
Physical Sciences →  Computer Science →  Artificial Intelligence

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