Predicting Fluctuations in Cryptocurrency Transactions Based on User Comments and Replies

Youngbin Kim · Jun Gi Kim · Jaeho Im · Tae Hyeong Kim · Shin-Jin Kang · Chang‐Hun Kim

286 citations0/0 files storedPLoS ONE

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Stock Market Forecasting Methods Blockchain Technology Applications and Security Sentiment Analysis and Opinion Mining

Abstract

This paper proposes a method to predict fluctuations in the prices of cryptocurrencies, which are increasingly used for online transactions worldwide. Little research has been conducted on predicting fluctuations in the price and number of transactions of a variety of cryptocurrencies. Moreover, the few methods proposed to predict fluctuation in currency prices are inefficient because they fail to take into account the differences in attributes between real currencies and cryptocurrencies. This paper analyzes user comments in online cryptocurrency communities to predict fluctuations in the prices of cryptocurrencies and the number of transactions. By focusing on three cryptocurrencies, each with a large market size and user base, this paper attempts to predict such fluctuations by using a simple and efficient method.

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References

2011Twitter mood predicts the stock market 2015What Are the Main Drivers of the Bitcoin Price? Evidence from Wavelet Coherence Analysis 2013BitCoin meets Google Trends and Wikipedia: Quantifying the relationship between phenomena of the Internet era 2000A bivariate causality between stock prices and exchange rates: evidence from recent Asianflu☆2014The digital traces of bubbles: feedback cycles between socio-economic signals in the Bitcoin economy 2013“When perhaps the real problem is money itself!”: the practical materiality of Bitcoin 2010Why would online gamers share their innovation-conducive knowledge in the online game user community? Integrating individual motivations and social capital perspectives

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