Aspect-Opinion Sentiment Alignment for Cross-Domain Sentiment Analysis (Student Abstract)

Abstract

Cross-domain sentiment analysis (SA) has recently attracted significant attention, which can effectively alleviate the problem of lacking large-scale labeled data for deep neural network based methods. However, exiting unsupervised cross-domain SA models ignore the relation between the aspect and opinion, which suffer from the sentiment transfer error problem. To solve this problem, we propose an aspect-opinion sentiment alignment SA model and extensive experiments are conducted to evaluate the effectiveness of our model.