Market Signals from Social Media

73 Pages Posted: 10 Apr 2025

See all articles by J. Anthony Cookson

J. Anthony Cookson

University of Colorado at Boulder - Leeds School of Business

Runjing Lu

University of Toronto

William Mullins

University of California, San Diego (UCSD)

Marina Niessner

Indiana University - Kelley School of Business - Department of Finance

Date Written: March 20, 2025

Abstract

This paper develops daily market-wide sentiment and attention indexes derived from millions of posts across major investor social media platforms. We find that sentiment extrapolates from past market-wide returns and exhibits a strong reversal. In contrast, attention predicts negative returns as a continuation of previous trends. The two indexes have distinct predictions for aggregate trading: abnormal trading rises when sentiment is low and attention is high. To identify the drivers of attention and sentiment, we use a shock to data sharing networks: We find sentiment spreads through real firm connections while attention does not. Moreover, attention rises after abnormally high trading, while sentiment rises after abnormally high returns. This extrapolative return pattern is asymmetric, primarily driven by negative market jumps. These findings provide new evidence on the daily market dynamics of sentiment and attention.

Keywords: Sentiment, Attention, Market-wide Signals, Social Media

JEL Classification: G12, E71, G41

Suggested Citation

Cookson, J. Anthony and Lu, Runjing and Mullins, William and Niessner, Marina, Market Signals from Social Media (March 20, 2025). FEB-RN Research Paper No. 63/2025, Available at SSRN: https://ssrn.com/abstract=5187350 or http://dx.doi.org/10.2139/ssrn.5187350

J. Anthony Cookson

University of Colorado at Boulder - Leeds School of Business ( email )

Boulder, CO 80309-0419
United States

Runjing Lu

University of Toronto ( email )

105 St George Street
Toronto, Ontario M5S 3G8
Canada

William Mullins (Contact Author)

University of California, San Diego (UCSD) ( email )

9500 Gilman Drive
Mail Code 0502
La Jolla, CA 92093-0112
United States

Marina Niessner

Indiana University - Kelley School of Business - Department of Finance

1309 E. 10th St
Bloomington, IN 47405
United States

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
511
Abstract Views
1,721
Rank
118,681
PlumX Metrics