How Does Social Media Impact Bitcoin Value? A Test of the Silent Majority Hypothesis

Feng Mai; Zhe Shan; Qing Bai; Xin (Shane) Wang; Roger H. L. Chiang

doi:10.1080/07421222.2018.1440774

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How Does Social Media Impact Bitcoin Value? A Test of the Silent Majority Hypothesis

Journal article

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How Does Social Media Impact Bitcoin Value? A Test of the Silent Majority Hypothesis

Feng Mai, Zhe Shan, Qing Bai, Xin (Shane) Wang and Roger H. L. Chiang

Journal of management information systems, Vol.35(1), pp.19-52

01/01/2018

DOI: 10.1080/07421222.2018.1440774

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Abstract

Bitcoin's emergence has the potential to pave the way for a technological revolution in financial markets. What determines its valuation is an important open question with far-reaching business and policy implications. Building on information systems and finance literature, we examine the dynamic interactions between social media and the monetary value of bitcoin using textual analysis and vector error correction models. We show that more bullish forum posts are associated with higher future bitcoin values. Interestingly, social media's effects on bitcoin are driven primarily by the silent majority, the 95 percent of users who are less active and whose contributions amount to less than 40 percent of total messages. In addition, messages on an Internet forum, relative to tweets, have a stronger impact on future bitcoin value. Overall, our findings reveal that social media sentiment is an important predictor in determining bitcoin's valuation, but not all social media messages are of equal impact. This study offers new insights into the digital currency market and the economic impact of social media.

Business & Economics

Computer Science

Computer Science, Information Systems

Information Science & Library Science

Management

Science & Technology

Social Sciences

Technology

Details

Title: Subtitle: How Does Social Media Impact Bitcoin Value? A Test of the Silent Majority Hypothesis
Creators: Feng Mai - Stevens Institute of Technology
Zhe Shan - University of Cincinnati
Qing Bai - Dickinson Coll, Dept Int Business & Management, Carlisle, PA 17013 USA
Xin (Shane) Wang - Western Univ, Ivey Business Sch, London, ON, Canada
Roger H. L. Chiang - University of Cincinnati
Resource Type: Journal article
Publication Details: Journal of management information systems, Vol.35(1), pp.19-52
Publisher: Taylor & Francis
DOI: 10.1080/07421222.2018.1440774
ISSN: 0742-1222
eISSN: 1557-928X
Number of pages: 34
Language: English
Date published: 01/01/2018
Academic Unit: Business Analytics
Record Identifier: 9984701723702771

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