🔗 Who cites «OMAM at SemEval-2017 Task 4: Evaluation of English State-of-the-Art Sentiment Analysis Models for Arabic and a New Topic-based Model»

6 papers of our library cite it (of the 149,439 whose bibliographies we read) · 6 with a page here, the most cited first · ← back to «OMAM at SemEval-2017 Task 4: Evaluation of English State-of-the-Art Sentiment Analysis Models for Arabic and a New Topic-based Model»

1. SemEval-2017 Task 4: Sentiment Analysis in TwitterInternational Workshop on Semantic Evaluation (SemEval)Sara Rosenthal, Noura Farra, Preslav Nakov2017 · 1,163 citations
2. ArSentD-LEV: A Multi-Topic Corpus for Target-based Sentiment Analysis in Arabic Levantine TweetsarXiv:1906.01830Ramy Baly, Alaa Khaddaj, Hazem Hajj, et al.2019 · 61 citations
3. EmoWordNet: Automatic Expansion of Emotion Lexicon Using English WordNetJoint Conference on Lexical and Computational Semantics (*SEM)Gilbert Badaro, Hussein Jundi, Hazem Hajj, et al.2018 · 43 citations
4. Empirical evaluation of shallow and deep learning classifiers for Arabic sentiment analysisACM Transactions on Asian and Low-Resource Language Information ProcessingAli Bou Nassif, Abdollah Masoud Darya, Ashraf Elnagar2021 · 34 citations
5. Modern Trends in Arabic Sentiment Analysis: A SurveyTraitement Automatique des LanguesHala Mulki, Hatem Haddad, Ismail Babaoğlu2017 · 12 citations
6. OMAM at SemEval-2017 Task 4: English Sentiment Analysis with Conditional Random FieldsInternational Workshop on Semantic Evaluation (SemEval)Chukwuyem Onyibe, Nizar Habash2017 · 12 citations

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