Proposed aspect based sentiment analysis system for English reviews

Abstract EN

Reviews are a crucial source of opinions that may influence the decision in many areas.

So there is a need for an algorithm that is efficient in understanding the aspects that the reviewers have focused on in their reviews and comments on social networks or other web applications.

This paper submits a proposed approach for aspect-based sentiment analysis that consists of two steps; the first step is by a proposed p_chunker algorithm for aspect extraction using Latent Dirchilet Analysis and noun phrase chunking, the second step is sentiment analysis using a proposed hybrid algorithm that depending on both lexicon and supervised sentiment analysis to specify the sentiment for extracted aspects.

The proposed paradigm is tested using standard datasets from kaggle for both aspect extraction and sentiment analysis, the result show efficacy in the proposed method.