Deep learning-based sentiment classification of evaluative text based on Multi-feature fusion

作者：

Highlights：

• A novel deep-learning-based method for sentiment classification.

• Rich feature set using word embedding, sentiment, statistical, linguistic knowledge.

• It integrates sentence type, contextual polarity, word sense, sentiment shifter rules.

• Results displayed that the method is to be preferred over other methods.

摘要

•A novel deep-learning-based method for sentiment classification.•Rich feature set using word embedding, sentiment, statistical, linguistic knowledge.•It integrates sentence type, contextual polarity, word sense, sentiment shifter rules.•Results displayed that the method is to be preferred over other methods.

论文关键词：Deep learning,Sentiment analysis,Natural language processing,Neural network

论文评审过程：Received 6 September 2018, Revised 24 January 2019, Accepted 28 February 2019, Available online 20 March 2019, Version of Record 20 March 2019.

论文官网地址：https://doi.org/10.1016/j.ipm.2019.02.018