Encoding Sentiment Information into Word Vectors for Sentiment Analysis

Zhe Ye, Fang Li, Timothy Baldwin
2018 International Conference on Computational Linguistics  
General-purpose pre-trained word embeddings have become a mainstay of natural language processing, and more recently, methods have been proposed to encode external knowledge into word embeddings to benefit specific downstream tasks. The goal of this paper is to encode sentiment knowledge into pre-trained word vectors to improve the performance of sentiment analysis. Our proposed method is based on a convolutional neural network and an external sentiment lexicon. Experiments on four popular
more » ... ment analysis datasets show that this method improves the accuracy of sentiment analysis compared to a number of benchmark methods.
dblp:conf/coling/YeLB18 fatcat:tzeajd5ii5fk5fnk4k2kamt2bu