دورية أكاديمية

Cryptocurrency ecosystems and social media environments: An empirical analysis through Hawkes’ models and natural language processing

التفاصيل البيبلوغرافية
العنوان: Cryptocurrency ecosystems and social media environments: An empirical analysis through Hawkes’ models and natural language processing
المؤلفون: Marco Ortu, Stefano Vacca, Giuseppe Destefanis, Claudio Conversano
المصدر: Machine Learning with Applications, Vol 7, Iss , Pp 100229- (2022)
بيانات النشر: Elsevier, 2022.
سنة النشر: 2022
المجموعة: LCC:Cybernetics
LCC:Electronic computers. Computer science
مصطلحات موضوعية: Cryptocurrencies, Social media analysis, Fundamental analysis, Forecasting price movements, Hawkes model, Cybernetics, Q300-390, Electronic computers. Computer science, QA75.5-76.95
الوصف: We analyse, using a mixture of statistical models and natural language process techniques, what happened in social media from June 2019 onwards to understand the relationships between Cryptocurrencies’ prices and social media, focusing on the rise of the Bitcoin and Ethereum prices. In particular, we identify and model the relationship between the cryptocurrencies market price changes, and sentiment and topic discussion occurrences on social media, using Hawkes’ Model. We find that some topics occurrences and rise of sentiment in social media precedes certain types of price movements. Specifically, discussions concerning governments, trading, and Ethereum cryptocurrency as an exchange currency appear to negatively affect Bitcoin and Ethereum prices. Those concerning investments, appear to explain price rises, whilst discussions related to new decentralized realities and technological applications explain price falls. Finally, we validate our model using a real case study: the already famous case of ”Wallstreetbet and GameStop”11 https://www.economist.com/finance-and-economics/2021/02/06/how-wallstreetbets-works. that took place in January 2021.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2666-8270
Relation: http://www.sciencedirect.com/science/article/pii/S2666827021001158; https://doaj.org/toc/2666-8270
DOI: 10.1016/j.mlwa.2021.100229
URL الوصول: https://doaj.org/article/24c1b5ba55ae4ec6a062db8f058b2684
رقم الأكسشن: edsdoj.24c1b5ba55ae4ec6a062db8f058b2684
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:26668270
DOI:10.1016/j.mlwa.2021.100229