User sentiment analysis,as an important task in the field of natural language processing,aims to automatically identify emotional tendencies from user-generated text content.A user sentiment analysis method based on Long Short-Term Memory(LSTM)network is proposed,which has achieved significant results in modeling text sequences and sentiment classification.The pre-trained word vector model is used to capture word semantics and the LSTM model is used to model text sequences.After training on a dataset containing 119 988 text data samples,the LSTM model achieves an accuracy of 99.13％in user sentiment analysis,which can achieve the purpose of classification well.
维普
万方数据
