The Effect of Tweets Made by Cryptocurrency Opinion Leaders on Bitcoin Prices

  • Hamza  
N/ACitations
Citations of this article
16Readers
Mendeley users who have this article in their library.

Abstract

Rapid technological advancements in the last few decades have given rise to various new products and fields, such as cryptocurrencies, social media and sentiment analysis. The massive surge in internet usage has caused organizations and investors to increasingly base their decisions on content placed on social media platforms which are flooded with data from its users. One of those platforms is twitter, a micro-blogging platform which allows people to share their opinions in a limited number of characters. Certain users on these platforms have the ability to influence other users' decision making, including investing. Although stock market prediction through sentiment analysis has been researched often, the amount of research done on prediction Bitcoin prices is relatively low. Furthermore, there is a gap in existing research in which samples are not limited to users that have more knowledge than individual investors. This paper uses sentiment analysis on tweets made be cryptocurrency influencers to see whether they can be used to predict Bitcoin price fluctuations. This paper, additionally researches differences in predictive capabilities between regions and differences in predictive capabilities between a bear and a bull market. The results in indicate that tweets made by cryptocurrency influencers contain statistically significant information about the future value of bitcoin. Thus, analyzing those tweets to exploit profitable opportunities can be worthwhile.

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Cite

CITATION STYLE

APA

Hamza,   Shakirullah. (2020). The Effect of Tweets Made by Cryptocurrency Opinion Leaders on Bitcoin Prices. Saudi Journal of Economics and Finance, 4(12), 569–589. https://doi.org/10.36348/sjef.2020.v04i12.005

Readers' Seniority

Tooltip

PhD / Post grad / Masters / Doc 5

100%

Readers' Discipline

Tooltip

Business, Management and Accounting 2

40%

Computer Science 1

20%

Social Sciences 1

20%

Medicine and Dentistry 1

20%

Article Metrics

Tooltip
Mentions
News Mentions: 2

Save time finding and organizing research with Mendeley

Sign up for free