Predicting Fluctuations in Cryptocurrency Transactions Based on User Comments and Replies
By Young Bin Kim, Jun Gi Kim, Wook Kim, Jaeho Im, Tae Hyeong Kim, Shinjin Kang, C. Kim. 2016
268 citations recorded by the source corpus.
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.
Subfields: Information Systems, Statistical and Nonlinear Physics
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In Information Systems
In Statistical and Nonlinear Physics
Citations in the corpus
- Finding attractive technical patterns in cryptocurrency markets (2018, background): “The literature on automatic trading of cryptocurrency is expanding at the moment [12,22].”
- Cryptocurrency trading: a comprehensive survey (2020, background): “[149] analysed user comments and replies in online communities and its connection with cryptocurrency volatility.”