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

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.

Authors

Institutions

Publication Details

Journal
SAGE Open
Published
2025-01-01
DOI
https://doi.org/10.1177/21582440251328535
Primary Topic
Sentiment Analysis and Opinion Mining
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Hosung Son, Qing Liu
SAGE Open
Sentiment Analysis and Opinion Mining
article

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

Hosung Son, Qing Liu
article en

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.

SAGE OpenVol. 15(1)
Huainan Normal University (CN), Pukyong National University (KR)
National Research Foundation of Korea
Openalex Percentile: Top 97%
Sentiment Analysis and Opinion Mining
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.