Advanced social media sentiment analysis for short‐term cryptocurrency price prediction. Issue 2 (21st November 2019)

• Record Type: Journal Article
• Authors: Wołk, Krzysztof
• Is Part Of: Expert systems. Volume 37:Issue 2(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2019-11-21
• Subjects: cryptocurrencies -- machine learning -- sentiment analysis -- social media -- speculative models; Expert systems (Computer science); 006.33
• DOI: 10.1111/exsy.12493
• Languages: English
• ISSNs: 0266-4720

Abstract

Abstract: In recent years, the scrutiny of bitcoin and other cryptocurrencies as legal and regulated components of financial systems has been increasing. Bitcoin is currently one of the largest cryptocurrencies in terms of capital market share. Therefore, this study proposes that sentiment analysis can be used as a computational tool to predict the prices of bitcoin and other cryptocurrencies for different time intervals. A key characteristic of the cryptocurrency market is that the fluctuation of currency prices depends on people's perceptions and opinions, not institutional money regulation. Therefore, analysing the relationship between social media and web search is crucial for cryptocurrency price prediction. This study uses Twitter and Google Trends to forecast the short‐term prices of the primary cryptocurrencies, as these social media platforms are used to influence purchasing decisions. The study adopts and interpolates a unique multimodel approach to analyse the impact of social media on cryptocurrency prices. Our results prove that people's psychological and behavioural attitudes have a significant impact on the highly speculative cryptocurrency prices.