Unveiling underlying patterns, drivers and anomalies in cryptocurrency price dynamics through feature fusion of financial indicators and sentiment fluctuations

Unveiling underlying patterns, drivers and anomalies in cryptocurrency price dynamics through feature fusion of financial indicators and sentiment fluctuations

This thesis is submitted in partial fulfillment of the requirements for the degree of Master of Science in Computer Science, 2024.

Bibliographische Detailangaben
1. Verfasser:	Rabbi, Md. Nafis
Weitere Verfasser:	Alam, Md. Golam Rabiul
Format:	Abschlussarbeit
Sprache:	English
Veröffentlicht:	Brac University 2024
Schlagworte:	Logistic regression Random forest regressor Sentiment analysis Naive Bayes Gaussian Data fusion Bitcoin. Cryptocurrencies > Prices
Online Zugang:	http://hdl.handle.net/10361/24031

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