Deep Learning for Aspect Based Sentiment Analysis: A Comparative Review
Abstract The increasing volume of user generated content on the web has made sentiment analysis an important tool for the extraction of information about the human emotional state. A current research focus for sentiment analysis is the improvement of granularity at aspect level, representing two distinct aims: aspect extraction and sentiment classification of product reviews and sentiment classification of target dependent tweets. Deep learning approaches have emerged as a prospect for achieving these aims with their ability to capture both syntactic and semantic features of text without requirements for high level feature engineering, as is the case in earlier methods. In this article, we aim to provide a comparative review of deep learning for aspect based sentiment analysis to place different approaches in context.
Expert Syst. Appl.