Affiliations: [a] Miracl, University of Sfax, Sfax, Tunisia | [b] Higher Institute of Computer Science and Multimedia of Gabes, Gabes, Tunisia | [c] Higher Institute of Computer Science and Multimedia of Sfax, Sfax, Tunisia
Correspondence:
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Corresponding author: Trugui Sana, Miracl, University of Sfax, Sfax, Tunisia. E-mail: truguisana0@gmail.com.
Abstract: Nowadays, sentiment analysis has been a very active research area with the increase of social media data. It presents a very useful task for product evaluation, social recommendation and popularity analysis. It constitutes also a crucial move towards natural language processing (NLP) domains. Our main goal is to identify sentiments towards aspect in the sentence. An aspect presents a specific entity or object features (price, product quality, etc.). Therefore, its analysis requires two primordial steps: extract entity aspects and identify the sentiments from all these aspects. In our research work, we propose a new hybrid method to detect sentiments towards aspects. We start with a machine learning method to detect the different aspects within a given sentence, followed by a rule based method to identify sentiments within these aspects. The evaluation of our hybrid system based on a reference dataset of Arabic Hotels’ reviews Semantic Evaluation-2016 shows that our system outperforms baseline research to achieve encouraging results (96% of F-score).
