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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 populardblp:conf/coling/YeLB18 fatcat:tzeajd5ii5fk5fnk4k2kamt2bu