Global cryptocurrency trend prediction using social media
dc.authorid | Cengiz, Korhan/0000-0001-6594-8861 | |
dc.authorid | Manoharan, Poongodi/0000-0001-6801-6138 | |
dc.authorwosid | Cengiz, Korhan/HTN-8060-2023 | |
dc.contributor.author | Poongodi, M. | |
dc.contributor.author | Nguyen, Tu N. | |
dc.contributor.author | Hamdi, Mounir | |
dc.contributor.author | Cengiz, Korhan | |
dc.date.accessioned | 2024-06-12T10:58:55Z | |
dc.date.available | 2024-06-12T10:58:55Z | |
dc.date.issued | 2021 | |
dc.department | Trakya Üniversitesi | en_US |
dc.description.abstract | This paper aims to investigate the global crypto-currency price movement trends with respect to the social media communication data. The idea is to analyze the topical trends in the online communities and social media platforms to understand and extract insights that could be used to predict the price fluctuations in crypto-currencies. The hypothesis rests in finding the empirical evidence to exploit the relationship between price variations and social media activities. Such models and insights will help us better understand the crypto currency ecosystems in context of social media behavior which can be used for real-time trading systems. | en_US |
dc.identifier.doi | 10.1016/j.ipm.2021.102708 | |
dc.identifier.issn | 0306-4573 | |
dc.identifier.issn | 1873-5371 | |
dc.identifier.issue | 6 | en_US |
dc.identifier.scopus | 2-s2.0-85112483852 | en_US |
dc.identifier.scopusquality | Q1 | en_US |
dc.identifier.uri | https://doi.org/10.1016/j.ipm.2021.102708 | |
dc.identifier.uri | https://hdl.handle.net/20.500.14551/20247 | |
dc.identifier.volume | 58 | en_US |
dc.identifier.wos | WOS:000701651800001 | en_US |
dc.identifier.wosquality | Q1 | en_US |
dc.indekslendigikaynak | Web of Science | en_US |
dc.indekslendigikaynak | Scopus | en_US |
dc.language.iso | en | en_US |
dc.publisher | Elsevier Sci Ltd | en_US |
dc.relation.ispartof | Information Processing & Management | en_US |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | Cryptocurrency | en_US |
dc.subject | Social Media | en_US |
dc.subject | Machine Learning | en_US |
dc.title | Global cryptocurrency trend prediction using social media | en_US |
dc.type | Article | en_US |