Cryptocurrency Prediction and Analysis between Supervised and Unsupervised Learning with XAI | |
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Author | |
Abstract |
The stock market is a topic that is of interest to all sorts of people. It is a place where the prices change very drastically. So, something needs to be done to help the people risking their money on the stock market. The public s opinions are crucial for the stock market. Sentiment is a very powerful force that is constantly changing and having a significant impact. It is reflected on social media platforms, where almost the entire country is active, as well as in the daily news. Many projects have been done in the stock prediction genre, but since sentiments play a big part in the stock market, making predictions of prices without them would lead to inefficient predictions, and hence Sentiment analysis is very important for stock market price prediction. To predict stock market prices, we will combine sentiment analysis from various sources, including News and Twitter. Results are evaluated for two different cryptocurrencies: Ethereum and Solana. Random Forest achieved the best RMSE of 13.434 and MAE of 11.919 for Ethereum. Support Vector Machine achieved the best RMSE of 2.48 and MAE of 1.78 for Solana. |
Year of Publication |
2023
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Date Published |
oct
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URL |
https://ieeexplore.ieee.org/document/10346583
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DOI |
10.1109/ICBDS58040.2023.10346583
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Google Scholar | BibTeX | DOI |