Predicting Fluctuations in Cryptocurrency Transactions Based on User Comments and Replies
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kim, Young Bin | - |
dc.contributor.author | Kim, Jun Gi | - |
dc.contributor.author | Kim, Wook | - |
dc.contributor.author | Im, Jae Ho | - |
dc.contributor.author | Kim, Tae Hyeong | - |
dc.contributor.author | Kang, Shin Jin | - |
dc.contributor.author | Kim, Chang Hun | - |
dc.date.accessioned | 2021-09-03T21:06:29Z | - |
dc.date.available | 2021-09-03T21:06:29Z | - |
dc.date.created | 2021-06-18 | - |
dc.date.issued | 2016-08-17 | - |
dc.identifier.issn | 1932-6203 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/87807 | - |
dc.description.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. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | PUBLIC LIBRARY SCIENCE | - |
dc.subject | CLASSIFICATION | - |
dc.subject | PATTERNS | - |
dc.title | Predicting Fluctuations in Cryptocurrency Transactions Based on User Comments and Replies | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Kim, Chang Hun | - |
dc.identifier.doi | 10.1371/journal.pone.0161197 | - |
dc.identifier.scopusid | 2-s2.0-84984830356 | - |
dc.identifier.wosid | 000381487600073 | - |
dc.identifier.bibliographicCitation | PLOS ONE, v.11, no.8 | - |
dc.relation.isPartOf | PLOS ONE | - |
dc.citation.title | PLOS ONE | - |
dc.citation.volume | 11 | - |
dc.citation.number | 8 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Science & Technology - Other Topics | - |
dc.relation.journalWebOfScienceCategory | Multidisciplinary Sciences | - |
dc.subject.keywordPlus | CLASSIFICATION | - |
dc.subject.keywordPlus | PATTERNS | - |
dc.subject.keywordAuthor | Forecasting | - |
dc.subject.keywordAuthor | Crawling | - |
dc.subject.keywordAuthor | Machine learning | - |
dc.subject.keywordAuthor | Social media | - |
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