Sentiment Analysis for colloquial Arabic Language | ||||
| النشرة المعلوماتية في الحاسبات والمعلومات | ||||
| Article 2, Volume 1, Issue 3 - Serial Number 20190103, October 2019, Page 7-11 PDF (332.85 K) | ||||
| Document Type: المقالة الأصلية | ||||
| DOI: 10.21608/fcihib.2019.107519 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
| Mohamed A.Rahim; Mohamed Nagy; Mohamed Sayed; Mohamed El-Bahy; Moataz Lotfy; Hesham Salama; Ensaf Hussein Mohamed | ||||
| Faculty of Computers and Artificial Intelligence, Helwan University, Cairo, Egypt | ||||
| Abstract | ||||
| Social media is a huge source of information; it is increasingly being used by governments, companies, and marketers to understand how the crowd thinks. Sentiment analysis is a research field that analyzes people’s opinions, sentiments, evaluations, appraisals, attitudes, and emotions towards entities such as products, services, organizations, individuals, issues, events, topics, and their attributes Arabic Sentiment Ontology (ASO) that contains different words that express feelings and how strongly these words express these feelings. In this paper, we proposed a new lexicon-based model for Arabic sentiment analysis with the support of the Vader Module, the accuracy of the model was 86.6%. | ||||
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