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

By Feng Mai, Zhe Shan, Qing Bai, Xin (Shane) Wang, Roger H. L. Chiang. Journal of Management Information Systems, 2018

300 citations recorded by the source corpus.

Subfields: Information Systems, Management Information Systems, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/7677a0070f604e97bc7544c168f84d20ebb26791

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Information Systems

1. Olivier Kraaijeveld
2. J. Smedt
3. David Mhlanga

In Management Information Systems

1. Robert J. Kauffman
2. Peter Gomber
3. David Mhlanga

In Management Science and Operations Research

1. Robert J. Kauffman
2. Olivier Kraaijeveld
3. J. Smedt
4. Robert G. Fichman

Citations in the corpus

• The predictive power of public Twitter sentiment for forecasting cryptocurrency prices (2020, background): “dividends) and hence have no intrinsic value, as their value is only determined by the expectations of a future resale value (Silverman et al., 2017; Mai et al., 2018).”
• On the Fintech Revolution: Interpreting the Forces of Innovation, Disruption, and Transformation in Financial Services (2018, background): “[106] explore the extent to which social media chatter influences Bitcoin price volatility, and whether longer blog posts or brief tweets have differential impacts.”