소셜 감성과 암호화폐 가격 간의 관계 분석: 빅데이터를 활용한 계량경제적 분석

An Analysis of Relationship between Social Sentiments and Cryptocurrency Price: An Econometric Analysis with Big Data

초록

Around the end of 2017, the investment fever for cryptocurrencies-especially Bitcoin-has started all over the world. Especially, South Korea has been at the center of this phenomenon. Sinceit was difficult to find the profitable investment opportunities, people have started to see the cryptocurrency markets as an alternative investment objects. However, the cryptocurrency fever inSouth Korea is mostly based on psychological phenomenon due to expectation of short-term profits and social atmosphere rather than intrinsic value of the assets. Therefore, this study aimed to analyze influence of people’s social sentiment on price movement of cryptocurrency. The data was collected for 181 days from Nov 1st, 2017 to Apr 30th, 2018, especially focusing on Bitcoin-related post in Twitter along with price of Bitcoin in Bithumb/UPbit. After the collected data was refined into neutral, positive and negative words through sentiment analysis, the refined neutral, positive, and negative words were put into regression model in order to find out the impacts of social sentiments on Bitcoin price. After examining the relationship by the regression analyses and Granger Causality tests, we found that the positive sentiments had a positive relationship with Bitcoin price, while the negative words had a negative relation with it. Also, the causality test results show that there exist two-way causalities between social sentiment and Bitcoin price movement. Therefore, we were able to conclude that the Bitcoin investors’behaviors are affected by the changes of social sentiments.

키워드

비트코인암호화폐소셜 감성감성 사전감성 분석오피니언 마이닝Granger 인과관계BitcoinCryptocurrencySocial SentimentSentiment LexiconSentiment AnalysisOpinion MiningGranger Causality test
제목
소셜 감성과 암호화폐 가격 간의 관계 분석: 빅데이터를 활용한 계량경제적 분석
제목 (타언어)
An Analysis of Relationship between Social Sentiments and Cryptocurrency Price: An Econometric Analysis with Big Data
저자
유상이현지연이상용
DOI
10.14329/isr.2019.21.1.091
발행일
2019-02
저널명
Information Systems Review
21
1
페이지
91 ~ 111