--- title: "Who cites Sentiment Analysis For Modern — 15 citing papers" description: "15 papers of the Elamur Research library cite «Sentiment Analysis For Modern Standard Arabic And Colloquial», found in their bibliographies…" canonical: "https://research.elamur.ai/free/en/papers/ibrahim-2015-sentiment-analysis-modern-standard-arabic/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/ibrahim-2015-sentiment-analysis-modern-standard-arabic/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Sentiment Analysis For Modern Standard Arabic And…](https://md.research.elamur.ai/free/en/papers/ibrahim-2015-sentiment-analysis-modern-standard-arabic/) / cited by # Who cites «Sentiment Analysis For Modern Standard Arabic And Colloquial» 15 papers of our library cite it (of the 149,439 whose bibliographies we read) · 15 with a page here, the most cited first · [← back to «Sentiment Analysis For Modern Standard Arabic And Colloquial»](https://md.research.elamur.ai/free/en/papers/ibrahim-2015-sentiment-analysis-modern-standard-arabic/) 1. **[ASTD: Arabic Sentiment Tweets Dataset](https://md.research.elamur.ai/free/en/papers/nabil-2015-astd-arabic-sentiment-tweets-dataset/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Mahmoud Nabil, Mohamed Aly, Amir Atiya*2015 · 470 citations* 2. [**A review of sentiment analysis research in Arabic language arXiv:2005.12240**Oumaima Oueslati; Erik Cambria; Moez Ben HajHmida;, Habib Ounelli*2020 · 241 citations*](https://md.research.elamur.ai/free/en/papers/oueslati-2020-review-sentiment-analysis-research-arabic/) 3. **[A Combined CNN and LSTM Model for Arabic Sentiment Analysis](https://md.research.elamur.ai/free/en/papers/alayba-2018-combined-cnn-lstm-model-arabic/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Abdulaziz M. Alayba; Vasile Palade; Matthew England;, Rahat Iqbal*2018 · 217 citations* 4. **[Deep Learning Models for Sentiment Analysis in Arabic](https://md.research.elamur.ai/free/en/papers/sallab-2015-deep-learning-models-sentiment-analysis/) [Workshop on Arabic Natural Language Processing](https://md.research.elamur.ai/free/en/venues/workshop-on-arabic-natural-language-processing/)**Ahmad Al Sallab, Hazem Hajj, Gilbert Badaro, et al.*2015 · 162 citations* 5. **[Natural Language Processing for Dialectical Arabic: A Survey](https://md.research.elamur.ai/free/en/papers/shoufan-2015-natural-language-processing-dialectical-arabic/) [Workshop on Arabic Natural Language Processing](https://md.research.elamur.ai/free/en/venues/workshop-on-arabic-natural-language-processing/)**Abdulhadi Shoufan, Sumaya Alameri*2015 · 142 citations* 6. [**A Comparative Study of Feature Selection Methods for Dialectal Arabic Sentiment Classification Using Support Vector Machine arXiv:1902.06242 · IJCSNS International Journal of Computer Science and Network Security, VOL.19 No.1, January 2019, 167-176**Omar Al-Harbi*2019 · 27 citations*](https://md.research.elamur.ai/free/en/papers/al-harbi-2019-comparative-study-feature-selection-methods/) 7. **[Using objective words in the reviews to improve the colloquial arabic sentiment analysis](https://md.research.elamur.ai/free/en/papers/al-harbi-2017-using-objective-words-reviews-improve/) [International Journal on Natural Language Computing](https://md.research.elamur.ai/free/en/venues/international-journal-on-natural-language-computing/)**Omar Al-Harbi*2017 · 8 citations* 8. **[Gulf Arabic Linguistic Resource Building for Sentiment Analysis](https://md.research.elamur.ai/free/en/papers/adouane-2016-gulf-arabic-linguistic-resource-building/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Wafia Adouane, Richard Johansson*2016 · 7 citations* 9. **[Can Modern Standard Arabic Approaches be used for Arabic Dialects? Sentiment Analysis as a Case Study](https://md.research.elamur.ai/free/en/papers/kwaik-2019-can-modern-standard-arabic-approaches/) [Workshop on Arabic Corpus Linguistics](https://md.research.elamur.ai/free/en/venues/wacl/)**Kathrein Abu Kwaik, Stergios Chatzikyriakidis, Simon Dobnik*2019 · 6 citations* 10. **[Subjective Sentiment Analysis for Arabic Newswire Comments](https://md.research.elamur.ai/free/en/papers/bessou-2019-subjective-sentiment-analysis-arabic-newswire/) [Journal of Digital Information Management](https://md.research.elamur.ai/free/en/venues/journal-of-digital-information-management/)**Sadik Bessou, Rania Aberkane*2019 · 6 citations* 11. **[AraDIC: Arabic Document Classification Using Image-Based Character Embeddings and Class-Balanced Loss](https://md.research.elamur.ai/free/en/papers/daif-2020-aradic-arabic-document-classification-image/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mahmoud Daif, Shunsuke Kitada, Hitoshi Iyatomi*2020 · 4 citations* 12. **[Des représentations continues de mots pour l'analyse d'opinions en arabe: une étude qualitative (Word embeddings for Arabic sentiment analysis : a qualitative study)](https://md.research.elamur.ai/free/en/papers/barhoumi-2018-des-representations-continues-de-mots/) [JEP-TALN-RECITAL (the French-speaking conferences on speech and natural language processing)](https://md.research.elamur.ai/free/en/venues/jeptalnrecital/)**Amira Barhoumi, Nathalie Camelin, Yannick Estève*2018 · 2 citations* 13. [**Sentiment Analysis in Poems in Misurata Sub-dialect — A Sentiment Detection in an Arabic Sub-dialect arXiv:2109.07203**Azza Abugharsa*2021*](https://md.research.elamur.ai/free/en/papers/abugharsa-2021-sentiment-analysis-poems-misurata-sub/) 14. [**LEBANONUPRISING: a thorough study of Lebanese tweets arXiv:2009.14459**Reda Khalaf, Mireille Makary*2020*](https://md.research.elamur.ai/free/en/papers/khalaf-2020-lebanonuprising-thorough-study-lebanese-tweets/) 15. **[Plongements lexicaux spécifiques à la langue arabe : application à l'analyse d'opinions (Arabic-specific embedddings : application in Sentiment Analysis)](https://md.research.elamur.ai/free/en/papers/barhoumi-2019-plongements-lexicaux-specifiques-la-langue/) [JEP-TALN-RECITAL (the French-speaking conferences on speech and natural language processing)](https://md.research.elamur.ai/free/en/venues/jeptalnrecital/)**Amira Barhoumi, Nathalie Camelin, Chafik Aloulou, et al.*2019* - [← back to](https://md.research.elamur.ai/free/en/papers/ibrahim-2015-sentiment-analysis-modern-standard-arabic/) — Sentiment Analysis For Modern Standard Arabic And Colloquial