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Predicting Fluctuations in Cryptocurrency Transactions Based on User Comments and Replies

Authors
Kim, Young BinKim, Jun GiKim, WookIm, Jae HoKim, Tae HyeongKang, Shin JinKim, Chang Hun
Issue Date
17-8월-2016
Publisher
PUBLIC LIBRARY SCIENCE
Keywords
Forecasting; Crawling; Machine learning; Social media
Citation
PLOS ONE, v.11, no.8
Indexed
SCIE
SCOPUS
Journal Title
PLOS ONE
Volume
11
Number
8
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/87807
DOI
10.1371/journal.pone.0161197
ISSN
1932-6203
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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