Aspect Level Sentiment Analysis Based on Deep Learning and Ontologies

Aspect level sentiment analysis has received much attention by researchers over the last few years. It aims first to determine the aspects in a given text (e.g., a comment, a sentence, a review, etc.) and second to perform the sentiment analysis (i.e., determine the polarity, such as positive, negative, or neutral) of the corresponding text with respect to each aspect. In this paper, we propose an original method of sentiment analysis for Tunisian social media. Our method is mainly based on domain ontologies for aspect extraction and deep learning models for aspect sentiment classification. Evaluation results are very encouraging, since we outperformed the baseline method with an enhancement of 17% for the task of aspect level sentiment classification. © 2023, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.