A deep learning approach to predict crypto-currency price by evaluating sentiment and stock market correlations
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2023.
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Brac University
2023
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10361-192332023-08-01T21:02:10Z A deep learning approach to predict crypto-currency price by evaluating sentiment and stock market correlations Maliha, Miftahul Zannat Trisha, Ananya Subhra Tamzid Khan, Abu Mauze Das, Prasoon Shakil, Shuhanur Rahman Hossain, Muhammad Iqbal Rahman, Rafeed Department of Computer Science and Engineering, Brac University Crypto-currency Machine learning Bitcoin Sentiment analysis Prediction Stock Market Machine learning Digital currency This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2023. Cataloged from PDF version of thesis. Includes bibliographical references (pages 29-31). For the technological shift, advancing epoch towards cryptocurrency intensified the impactful method. Metaverse can originate the base operation into a diversified level. The extension of digital marketing contributes to blockchain technology more.Our research demonstrates, attested cryptocurrency price evaluation associated with the stock and sentiment. In our research, we have implemented various techniques to predict cryptocurrency prices. Crypto like bitcoin, ethereum and litecoin are the primary focus in this paper. Our research observes the fluctuation into the cryptocurrency prices. In our research procedure, we used the LSTM-GRU hybrid, ARIMA for time series prediction. The research follows sentiment analysis from the twitter scrapped data. The research provides cogent insights of cryptocurrency price prediction fluidity with the stock price and the twitter sentiment on following cryptocurrencies. Additionally, the data merge with the LSTM time series model depicts the cryptocurrency stock market and shows us the relationship between stock price, twitter sentiment and cryptocurrency price pertinence Miftahul Zannat Maliha Ananya Subhra Trisha Abu Mauze Tamzid Khan Prasoon Das Shuhanur Rahman Shakil B. Computer Science 2023-08-01T06:08:29Z 2023-08-01T06:08:29Z 2023 2023-01 Thesis ID: 22341041 ID: 20241062 ID: 19301045 ID: 18101603 ID: 18301243 http://hdl.handle.net/10361/19233 en Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 31 pages application/pdf Brac University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
Crypto-currency Machine learning Bitcoin Sentiment analysis Prediction Stock Market Machine learning Digital currency |
| spellingShingle |
Crypto-currency Machine learning Bitcoin Sentiment analysis Prediction Stock Market Machine learning Digital currency Maliha, Miftahul Zannat Trisha, Ananya Subhra Tamzid Khan, Abu Mauze Das, Prasoon Shakil, Shuhanur Rahman A deep learning approach to predict crypto-currency price by evaluating sentiment and stock market correlations |
| description |
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2023. |
| author2 |
Hossain, Muhammad Iqbal |
| author_facet |
Hossain, Muhammad Iqbal Maliha, Miftahul Zannat Trisha, Ananya Subhra Tamzid Khan, Abu Mauze Das, Prasoon Shakil, Shuhanur Rahman |
| format |
Thesis |
| author |
Maliha, Miftahul Zannat Trisha, Ananya Subhra Tamzid Khan, Abu Mauze Das, Prasoon Shakil, Shuhanur Rahman |
| author_sort |
Maliha, Miftahul Zannat |
| title |
A deep learning approach to predict crypto-currency price by evaluating sentiment and stock market correlations |
| title_short |
A deep learning approach to predict crypto-currency price by evaluating sentiment and stock market correlations |
| title_full |
A deep learning approach to predict crypto-currency price by evaluating sentiment and stock market correlations |
| title_fullStr |
A deep learning approach to predict crypto-currency price by evaluating sentiment and stock market correlations |
| title_full_unstemmed |
A deep learning approach to predict crypto-currency price by evaluating sentiment and stock market correlations |
| title_sort |
deep learning approach to predict crypto-currency price by evaluating sentiment and stock market correlations |
| publisher |
Brac University |
| publishDate |
2023 |
| url |
http://hdl.handle.net/10361/19233 |
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