Sentiment Analysis of User Comment Text based on LSTM

Taking the user-generated Chinese comment dataset on online platforms as the research object, we constructed word2vec word vectors using gensim and built a sentiment analysis model based on LSTM using the TensorFlow deep learning framework. From the perspective of mining user comment data on the platform, we analyzed the sentiment tendency of user comments, providing data support for hotels to understand consumers' real sentiment tendencies and improve their own service quality. Through analysis of the validation dataset results obtained by crawling the website, the accuracy of this LSTM model can reach up to 0.89, but there is still much room for improvement in the accuracy of sentiment analysis for some datasets. In future research, this model needs further optimization to obtain a stable and more accurate deep-learning model.