🔗 Who cites «A Characterization Study of Arabic Twitter Data with a Benchmarking for State-of-the-Art Opinion Mining Models»

11 papers of our library cite it (of the 149,439 whose bibliographies we read) · 11 with a page here, the most cited first · ← back to «A Characterization Study of Arabic Twitter Data with a Benchmarking for State-of-the-Art Opinion Mining Models»

1. EMA at SemEval-2018 Task 1: Emotion Mining for ArabicInternational Workshop on Semantic Evaluation (SemEval)Gilbert Badaro, Obeida El Jundi, Alaa Khaddaj, et al.2018 · 73 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. Combining BERT with Static Word Embeddings for Categorizing Social MediaWorkshop on Noisy User-generated TextIsraa Alghanmi, Luis Espinosa Anke, Steven Schockaert2020 · 40 citations
5. 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
6. OMAM at SemEval-2017 Task 4: Evaluation of English State-of-the-Art Sentiment Analysis Models for Arabic and a New Topic-based ModelInternational Workshop on Semantic Evaluation (SemEval)Ramy Baly, Gilbert Badaro, Ali Hamdi, et al.2017 · 33 citations
7. Improved Generalization of Arabic Text ClassifiersArabic Natural Language Processing Workshop (WANLP)Alaa Khaddaj, Hazem Hajj, Wassim El-Hajj2019 · 10 citations
8. A Comprehensive Survey of Contemporary Arabic Sentiment Analysis: Methods, Challenges, and Future DirectionsFindings of the Association for Computational LinguisticsZhiqiang Shi, Ruchit Agrawal2025 · 9 citations
9. Combining Context-Free and Contextualized Representations for Arabic Sarcasm Detection and Sentiment IdentificationArabic Natural Language Processing Workshop (WANLP)Amey Hengle, Atharva Kshirsagar, Shaily Desai, et al.2021 · 6 citations
10. Can Modern Standard Arabic Approaches be used for Arabic Dialects? Sentiment Analysis as a Case StudyWorkshop on Arabic Corpus LinguisticsKathrein Abu Kwaik, Stergios Chatzikyriakidis, Simon Dobnik2019 · 6 citations
11. Sentiment Analysis in Poems in Misurata Sub-dialect — A Sentiment Detection in an Arabic Sub-dialectarXiv:2109.07203Azza Abugharsa2021

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