Cryptocurrency ecosystems and social media environments: An empirical analysis through Hawkes’ models and natural language processing - CORE Reader
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e model these online discussionsusing the Hawkes Model to understand the mutual influence of online techni-cal discussion of the two leading cryptocurrencies where we analyse the occurrence ofparticular topics from social media content through dynamic topic modelling,that is an extension of Lat
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Summary
This paper explores the relationship between cryptocurrency market prices and social media discussions, specifically focusing on Bitcoin and Ethereum. The authors use the Hawkes Model to analyze the mutual influence of online technical discussions and apply dynamic topic modeling to identify potential hidden interactions between social media topics and cryptocurrency prices. They propose a cost-effective solution for a real-time alarm system that can support investors' decisions. The paper also mentions previous studies that have shown the relationship between Google searches and Bitcoin prices, as well as the polarization of sentiment on Twitter and its impact on Bitcoin prices.
Top Highlights
- e model these online discussionsusing the Hawkes Model to understand the mutual influence of online techni-cal discussion of the two leading cryptocurrencies
- where we analyse the occurrence ofparticular topics from social media content through dynamic topic modelling,that is an extension of Latent Dirichlet Allocation (LDA)
- features extracted from comments, and again we apply the Hawkes model toidentify possible hidden interactions between these features and cryptocurrencymarket prices
- Design of a cost-effective solution for a real-time alarm system that canbe used to support investors’ decisions
- Specification of a unique mixture of natural language processing, statis-tical model and pre-existing tools to promote and validate the researchhypothesis
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Research
Event Driven
economic
Paper
machine learning
Crypto
Domain
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