| Abstrakt: |
There has been a rise in interest in recent years in predicting cryptocurrency prices using deep learning and Twitter sentiments. In this approach, the sentiment of Twitter posts is used as a predictor of future cryptocurrency price movements, and deep learning algorithms are employed to make accurate predictions. However, this approach faces several challenges, including the quality of the data, the limited availability of training data, the complexity of the relationship between Twitter sentiments and cryptocurrency prices, the lack of interpretability of deep learning models, and the risk of overfitting. Despite these challenges, using Twitter sentiments and deep learning has shown promise in predicting cryptocurrency prices, and further research in this area may lead to more accurate and reliable models for pricing forecasts for cryptocurrencies. Based on user sentiment, the initiative aims to predict the movements of any cryptocurrency. It achieves this by comprehending the connection between the sentiments expressed in significant tweets and the price of the coin at the moment. Twitter data is gathered using Twython and the keywords #Bitcoin and #BTC. Utilizing pertinent searches, the Twitter API is used to extract tweets. The cryptocompare API was also used to get information on the current price of Bitcoin. [ABSTRACT FROM AUTHOR] |
