Review Mining for Experiential Products Incorporating Word2vec and Review Sentiment Tendencies

Abstract

In view of the difficulty in mining the characteristics of experience-based products, this paper proposes a method combining LDA and Word2vec to extract product features. This method uses the emotion dictionary to carry out fine-grained analysis on these features, which improves the defect that the effect of topic clustering is not obvious. The result shows that it can effectively mine the feature words with high relevance, and put forward more targeted suggestions for producers.