The project researches sentiment analysis on Twitter, with the goal of evaluating the positivity, negativity or neutrality of comments. Using Word Embeddings, an advanced method in natural language processing, our model achieved a high accuracy of 96.61%. The model was trained on Twitter data and tested on a data comment dataset from Binance.