Political Arabic Articles Orientation Using Rough Set Theory With Sentiment Lexicon

Sentiment analysis is an emerging research field that can be integrated with other domains, including data mining, natural language processing and machine learning. In political articles, it difficult to understand summarise the state or overall views due diversity size of social media information. A number studies were conducted in area sentiment analysis, especially using English texts, while Arabic received less attention literature. this study, we propose a detection model for orientation articles language. We introduce key assumptions model, present discuss obtained results, highlight issues still need explored further our understanding subjective sentences. The main purpose applying new approach based on Rough Set (RS) theory increase accuracy models recognizing articles. extensive simulation which demonstrate superiority proposed over algorithms. It shown performance significantly improves by adding discriminating features. To summarize, demonstrates 85.483%, when evaluating datasets, compared 72.58% 64.516% Support Vector Machines Naïve Bayes methods, respectively.