The purpose of this thesis is to predict cryptocurrency value, based on sentimental analysis of social media post. Social media has become a place where individuals are sharing the news rapidly. While, considering the financial commodity, the confidence of public is the specific commodity is the core base value. Hence, this thesis considers social media post on Twitter, Reddit and Crypto Compare platforms to perform sentiment analysis on the posts. This sentiment anaysis is used to predict the value of Bitcoin, Ethereum and Litcoin using machine learning models, such as, Decision Tree, Log Regression, Naive Bayes and Ensemble.
Lo scopo di questa tesi è prevedere il valore della criptovaluta, sulla base dell'analisi sentimentale dei post sui social media. I social media sono diventati un luogo in cui le persone condividono rapidamente le notizie. Mentre, considerando la merce finanziaria, la fiducia del pubblico è la merce specifica è il valore di base fondamentale. Quindi, questa tesi considera i post sui social media sulle piattaforme Twitter, Reddit e Crypto Compare per eseguire l'analisi del sentiment sui post. Questa analisi del sentiment viene utilizzata per prevedere il valore di Bitcoin, Ethereum e Litcoin utilizzando modelli di apprendimento automatico, come Decision Tree, Log Regression, Naive Bayes e Ensemble.
Predicting cryptocurrency value, based on sentimental analysis of social media post
KHAN, MOHSIN
2020/2021
Abstract
The purpose of this thesis is to predict cryptocurrency value, based on sentimental analysis of social media post. Social media has become a place where individuals are sharing the news rapidly. While, considering the financial commodity, the confidence of public is the specific commodity is the core base value. Hence, this thesis considers social media post on Twitter, Reddit and Crypto Compare platforms to perform sentiment analysis on the posts. This sentiment anaysis is used to predict the value of Bitcoin, Ethereum and Litcoin using machine learning models, such as, Decision Tree, Log Regression, Naive Bayes and Ensemble.File | Dimensione | Formato | |
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Thesis_Mohsin_2.pdf
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https://hdl.handle.net/10589/186810