A deep learning-based intelligent method for mining sentiment words in english translation texts

Abstract The current conventional sentiment lexicon mining methods mainly achieve lexical extraction by mining the sentiment features of words, which leads to poor mining effect due to the lack of sentiment lexicon construction. In this regard, the intelligent mining method of sentiment lexicon of English translation text based on deep learning is proposed. The intelligent mining algorithm is optimized by extracting lexical templates with generality, constructing sentiment lexicon, and building convolutional network to extract lexical features. The experimental results showed that this mining method had an accuracy of over 85% in mining emotional vocabulary in translated texts, which was higher than other algorithms. Meanwhile, the mining time required for this algorithm was not yet 4.5 min. The above results indicated that the proposed method had higher accuracy and faster speed in mining emotional vocabulary in English translation texts.