---
title: "Who cites Subjectivity and Sentiment — 63 citing papers"
description: "63 papers of the Elamur Research library cite «Subjectivity and Sentiment Analysis of Modern Standard Arabic», found in their bibliographies…"
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---
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# Who cites «Subjectivity and Sentiment Analysis of Modern Standard Arabic»

63 papers of our library cite it (of the 149,439 whose bibliographies we read) · 49 with a page here, the most cited first · [← back to «Subjectivity and Sentiment Analysis of Modern Standard Arabic»](https://md.research.elamur.ai/free/en/papers/mageed-2011-subjectivity-sentiment-analysis-modern-standard/)

1. **[Exploring Demographic Language Variations to Improve Multilingual Sentiment Analysis in Social Media](https://md.research.elamur.ai/free/en/papers/volkova-2013-exploring-demographic-language-variations-improve/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Svitlana Volkova, Theresa Wilson, David Yarowsky*2013 · 250 citations*
2. **[A Survey of Arabic Named Entity Recognition and Classification](https://md.research.elamur.ai/free/en/papers/shaalan-2014-survey-arabic-named-entity-recognition/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Khaled Shaalan*2014 · 242 citations*
3. [**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/)
4. **[A Large Scale Arabic Sentiment Lexicon for Arabic Opinion Mining](https://md.research.elamur.ai/free/en/papers/badaro-2014-large-scale-arabic-sentiment-lexicon/) [EMNLP Workshop on Arabic Natural Language Processing (ANLP)](https://md.research.elamur.ai/free/en/venues/emnlp-workshop-on-arabic-natural-language-processing-anlp/)**Gilbert Badaro, Ramy Baly, Hazem Hajj, et al.*2014 · 232 citations*
5. **[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*
6. **[Mazajak: An Online Arabic Sentiment Analyser](https://md.research.elamur.ai/free/en/papers/farha-2019-mazajak-online-arabic-sentiment-analyser/) [Arabic Natural Language Processing Workshop (WANLP)](https://md.research.elamur.ai/free/en/venues/wanlp/)**Ibrahim Abu Farha, Walid Magdy*2019 · 197 citations*
7. **[AWATIF: A Multi-Genre Corpus for Modern Standard Arabic Subjectivity and Sentiment Analysis](https://md.research.elamur.ai/free/en/papers/mageed-2012-awatif-multi-genre-corpus-modern/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Muhammad Abdul-Mageed, Mona Diab*2012 · 196 citations*
8. **[Subjectivity and Sentiment Analysis of Modern Standard Arabic and Arabic Microblogs](https://md.research.elamur.ai/free/en/papers/mourad-2013-subjectivity-sentiment-analysis-modern-standard/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Ahmed Mourad, Kareem Darwish*2013 · 188 citations*
9. **[Word Embeddings and Convolutional Neural Network for Arabic Sentiment Classification](https://md.research.elamur.ai/free/en/papers/dahou-2016-word-embeddings-convolutional-neural-network/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Abdelghani Dahou, Shengwu Xiong, Junwei Zhou, et al.*2016 · 177 citations*
10. **[An Arabic Twitter Corpus for Subjectivity and Sentiment Analysis](https://md.research.elamur.ai/free/en/papers/refaee-2014-arabic-twitter-corpus-subjectivity-sentiment/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Eshrag Refaee, Verena Rieser*2014 · 172 citations*
11. **[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*
12. **[SemEval-2016 Task 7: Determining Sentiment Intensity of English and Arabic Phrases](https://md.research.elamur.ai/free/en/papers/kiritchenko-2016-semeval-2016-task-7-determining/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Svetlana Kiritchenko, Saif Mohammad, Mohammad Salameh*2016 · 135 citations*
13. **[From Arabic Sentiment Analysis to Sarcasm Detection: The ArSarcasm Dataset](https://md.research.elamur.ai/free/en/papers/farha-2020-arabic-sentiment-analysis-sarcasm-detection/) [Workshop on Open-Source Arabic Corpora and Processing Tools with Shared Tasks](https://md.research.elamur.ai/free/en/venues/osact/)**Ibrahim Abu Farha, Walid Magdy*2020 · 132 citations*
14. **[Sentiment Analysis For Modern Standard Arabic And Colloquial](https://md.research.elamur.ai/free/en/papers/ibrahim-2015-sentiment-analysis-modern-standard-arabic/) [International Journal on Natural Language Computing](https://md.research.elamur.ai/free/en/venues/international-journal-on-natural-language-computing/)**Hossam S. Ibrahim, Sherif M. Abdou, Mervat Gheith*2015 · 115 citations*
15. [**SAMAR: A System for Subjectivity and Sentiment Analysis of Arabic Social Media Proceedings of the 3rd Workshop in Computational Approaches to Subjectivity and Sentiment Analysis**Muhammad Abdul-Mageed, Sandra Kuebler, Mona Diab*2012 · 115 citations*](https://md.research.elamur.ai/free/en/papers/mageed-2012-samar-system-subjectivity-sentiment-analysis/)
16. **[SANA: A Large Scale Multi-Genre, Multi-Dialect Lexicon for Arabic Subjectivity and Sentiment Analysis](https://md.research.elamur.ai/free/en/papers/mageed-2014-sana-large-scale-multi-genre/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Muhammad Abdul-Mageed, Mona Diab*2014 · 114 citations*
17. **[Overview of the WANLP 2021 Shared Task on Sarcasm and Sentiment Detection in Arabic](https://md.research.elamur.ai/free/en/papers/farha-2021-overview-wanlp-2021-shared-task/) [Arabic Natural Language Processing Workshop (WANLP)](https://md.research.elamur.ai/free/en/venues/wanlp/)**Ibrahim Abu Farha, Wajdi Zaghouani, Walid Magdy*2021 · 112 citations*
18. **[Sentiment Lexicons for Arabic Social Media](https://md.research.elamur.ai/free/en/papers/mohammad-2016-sentiment-lexicons-arabic-social-media/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Saif Mohammad, Mohammad Salameh, Svetlana Kiritchenko*2016 · 83 citations*
19. **[SLSA: A Sentiment Lexicon for Standard Arabic](https://md.research.elamur.ai/free/en/papers/eskander-2015-slsa-sentiment-lexicon-standard-arabic/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ramy Eskander, Owen Rambow*2015 · 72 citations*
20. **[A Characterization Study of Arabic Twitter Data with a Benchmarking for State-of-the-Art Opinion Mining Models](https://md.research.elamur.ai/free/en/papers/baly-2017-characterization-study-arabic-twitter-data/) [Arabic Natural Language Processing Workshop (WANLP)](https://md.research.elamur.ai/free/en/venues/wanlp/)**Ramy Baly, Gilbert Badaro, Georges El-Khoury, et al.*2017 · 67 citations*
21. **[LABR: A Large Scale Arabic Book Reviews Dataset](https://md.research.elamur.ai/free/en/papers/aly-2013-labr-large-scale-arabic-book/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mohamed Aly, Amir Atiya*2013 · 66 citations*
22. [**ArSentD-LEV: A Multi-Topic Corpus for Target-based Sentiment Analysis in Arabic Levantine Tweets arXiv:1906.01830**Ramy Baly, Alaa Khaddaj, Hazem Hajj, et al.*2019 · 61 citations*](https://md.research.elamur.ai/free/en/papers/baly-2019-arsentd-lev-multi-topic-corpus/)
23. [**Improving Sentiment Analysis in Arabic Using Word Representation arXiv:1803.00124 · Proc. 2nd International Workshop on Arabic and Derived Script Analysis and Recognition (ASAR '18), pp. 13-18. IEEE, 2018**Abdulaziz M. Alayba, Vasile Palade, Matthew England, et al.*2018 · 59 citations*](https://md.research.elamur.ai/free/en/papers/alayba-2018-improving-sentiment-analysis-arabic-using/)
24. **[Enabling Deep Learning of Emotion With First-Person Seed Expressions](https://md.research.elamur.ai/free/en/papers/alhuzali-2018-enabling-deep-learning-emotion-first/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Hassan Alhuzali, Muhammad Abdul-Mageed, Lyle Ungar*2018 · 41 citations*
25. [**LABR: A Large Scale Arabic Sentiment Analysis Benchmark arXiv:1411.6718**Mahmoud Nabil, Mohamed Aly, Amir Atiya*2014 · 41 citations*](https://md.research.elamur.ai/free/en/papers/nabil-2014-labr-large-scale-arabic-sentiment/)
26. **[OMAM at SemEval-2017 Task 4: Evaluation of English State-of-the-Art Sentiment Analysis Models for Arabic and a New Topic-based Model](https://md.research.elamur.ai/free/en/papers/baly-2017-omam-semeval-2017-task-4/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Ramy Baly, Gilbert Badaro, Ali Hamdi, et al.*2017 · 33 citations*
27. **[Idioms-Proverbs Lexicon for Modern Standard Arabic and Colloquial Sentiment Analysis](https://md.research.elamur.ai/free/en/papers/ibrahim-2015-idioms-proverbs-lexicon-modern-standard/) [International Journal of Computer Applications](https://md.research.elamur.ai/free/en/venues/international-journal-of-computer-applications/)**Hossam S. Ibrahim, Sherif M. Abdou, Mervat Gheith*2015 · 33 citations*
28. **[iLab-Edinburgh at SemEval-2016 Task 7: A Hybrid Approach for Determining Sentiment Intensity of Arabic Twitter Phrases](https://md.research.elamur.ai/free/en/papers/refaee-2016-ilab-edinburgh-semeval-2016-task/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Eshrag Refaee, Verena Rieser*2016 · 32 citations*
29. **[A Light Lexicon-based Mobile Application for Sentiment Mining of Arabic Tweets](https://md.research.elamur.ai/free/en/papers/badaro-2015-light-lexicon-based-mobile-application/) [Workshop on Arabic Natural Language Processing](https://md.research.elamur.ai/free/en/venues/workshop-on-arabic-natural-language-processing/)**Gilbert Badaro, Ramy Baly, Rana Akel, et al.*2015 · 32 citations*
30. **[Benchmarking Machine Translated Sentiment Analysis for Arabic Tweets](https://md.research.elamur.ai/free/en/papers/refaee-2015-benchmarking-machine-translated-sentiment-analysis/) [Conference of the North American Chapter of the Association for Computational Linguistics: Student Research Workshop](https://md.research.elamur.ai/free/en/venues/conference-of-the-north-american-chapter-of-the-association-for-computational/)**Eshrag Refaee, Verena Rieser*2015 · 31 citations*
31. [**Sentiment Analysis of Arabic Tweets: Feature Engineering and A Hybrid Approach arXiv:1805.08533**Nora Al-Twairesh, Hend Al-Khalifa, AbdulMalik Alsalman, et al.*2018 · 30 citations*](https://md.research.elamur.ai/free/en/papers/al-twairesh-2018-sentiment-analysis-arabic-tweets-feature/)
32. **[Exploring the Effects of Word Roots for Arabic Sentiment Analysis](https://md.research.elamur.ai/free/en/papers/oraby-2013-exploring-effects-word-roots-arabic/) [International Joint Conference on Natural Language Processing (IJCNLP)](https://md.research.elamur.ai/free/en/venues/ijcnlp/)**Shereen Oraby, Yasser El-Sonbaty, Mohamad Abou El-Nasr*2013 · 30 citations*
33. **[Evaluating ChatGPT and Bard AI on Arabic Sentiment Analysis](https://md.research.elamur.ai/free/en/papers/thubaity-2023-evaluating-chatgpt-bard-ai-arabic/) [Arabic Natural Language Processing Conference (ArabicNLP)](https://md.research.elamur.ai/free/en/venues/arabicnlp/)**Abdulmohsen Al-Thubaity, Sakhar Alkhereyf, Hanan Murayshid, et al.*2023 · 27 citations*
34. **[Evaluating Distant Supervision for Subjectivity and Sentiment Analysis on Arabic Twitter Feeds](https://md.research.elamur.ai/free/en/papers/refaee-2014-evaluating-distant-supervision-subjectivity-sentiment/) [EMNLP Workshop on Arabic Natural Language Processing (ANLP)](https://md.research.elamur.ai/free/en/venues/emnlp-workshop-on-arabic-natural-language-processing-anlp/)**Eshrag Refaee, Verena Rieser*2014 · 27 citations*
35. **[Machine Learning-Based Model for Sentiment and Sarcasm Detection](https://md.research.elamur.ai/free/en/papers/nayel-2021-machine-learning-based-model-sentiment/) [Arabic Natural Language Processing Workshop (WANLP)](https://md.research.elamur.ai/free/en/venues/wanlp/)**Hamada Nayel, Eslam Amer, Aya Allam, et al.*2021 · 25 citations*
36. [**Sentiment analysis for Arabic language: A brief survey of approaches and techniques arXiv:1809.02782**Mo'ath Alrefai, Hossam Faris, Ibrahim Aljarah*2018 · 24 citations*](https://md.research.elamur.ai/free/en/papers/alrefai-2018-sentiment-analysis-arabic-language-brief/)
37. **[Modern Trends in Arabic Sentiment Analysis: A Survey](https://md.research.elamur.ai/free/en/papers/mulki-2017-modern-trends-arabic-sentiment-analysis/) [Traitement Automatique des Langues](https://md.research.elamur.ai/free/en/venues/tal/)**Hala Mulki, Hatem Haddad, Ismail Babaoğlu*2017 · 12 citations*
38. [**A System for Extracting Sentiment from Large-Scale Arabic Social Data arXiv:1511.04661**Hao Wang, Vijay R. Bommireddipalli, Ayman Hanafy, et al.*2015 · 12 citations*](https://md.research.elamur.ai/free/en/papers/wang-2015-system-extracting-sentiment-large-scale/)
39. **[Morphology Without Borders: Clause-Level Morphology](https://md.research.elamur.ai/free/en/papers/goldman-2022-morphology-without-borders-clause-level/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Omer Goldman, Reut Tsarfaty*2022 · 11 citations*
40. **[AraBERT and Farasa Segmentation Based Approach For Sarcasm and Sentiment Detection in Arabic Tweets](https://md.research.elamur.ai/free/en/papers/wadhawan-2021-arabert-farasa-segmentation-based-approach/) [Arabic Natural Language Processing Workshop (WANLP)](https://md.research.elamur.ai/free/en/venues/wanlp/)**Anshul Wadhawan*2021 · 11 citations*
41. **[ThatiAR: Subjectivity Detection in Arabic News Sentences](https://md.research.elamur.ai/free/en/papers/suwaileh-2024-thatiar-subjectivity-detection-arabic-news/) [Proceedings of the International AAAI Conference on Web and Social Media](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-international-aaai-conference-on-web-and-social-media/)**Reem Suwaileh, Maram Hasanain, Fatema Hubail, et al.*2024 · 7 citations*
42. **[iCompass at Shared Task on Sarcasm and Sentiment Detection in Arabic](https://md.research.elamur.ai/free/en/papers/naski-2021-icompass-shared-task-sarcasm-sentiment/) [Arabic Natural Language Processing Workshop (WANLP)](https://md.research.elamur.ai/free/en/venues/wanlp/)**Malek Naski, Abir Messaoudi, Hatem Haddad, et al.*2021 · 7 citations*
43. **[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*
44. **[SMASH at StanceEval 2024: Prompt Engineering LLMs for Arabic Stance Detection](https://md.research.elamur.ai/free/en/papers/hariri-2024-smash-stanceeval-2024-prompt-engineering/) [Arabic Natural Language Processing Conference (ArabicNLP)](https://md.research.elamur.ai/free/en/venues/arabicnlp/)**Youssef Al Hariri, Ibrahim Abu Farha*2024 · 6 citations*
45. **[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*
46. [**Arabic Sentiment Analysis with Noisy Deep Explainable Model arXiv:2309.13731 · NLPIR 2023: 2023 7th International Conference on Natural Language Processing and Information Retrieval, Seoul, Republic of Korea, December 2023**Md. Atabuzzaman, Md Shajalal, Maksuda Bilkis Baby, et al.*2023 · 5 citations*](https://md.research.elamur.ai/free/en/papers/atabuzzaman-2023-arabic-sentiment-analysis-noisy-deep/)
47. **[SentiArabic: A Sentiment Analyzer for Standard Arabic](https://md.research.elamur.ai/free/en/papers/eskander-2018-sentiarabic-sentiment-analyzer-standard-arabic/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Ramy Eskander*2018 · 4 citations*
48. **[ARB-SEN at SemEval-2018 Task1: A New Set of Features for Enhancing the Sentiment Intensity Prediction in Arabic Tweets](https://md.research.elamur.ai/free/en/papers/nagoudi-2018-arb-sen-semeval-2018-task1/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**El Moatez Billah Nagoudi*2018 · 3 citations*
49. **[Dhati+: Fine-tuned Large Language Models for Arabic Subjectivity Evaluation](https://md.research.elamur.ai/free/en/papers/bellaouar-2025-dhati-fine-tuned-large-language/) [Language Resources and Evaluation](https://md.research.elamur.ai/free/en/venues/language-resources-and-evaluation/)**Slimane Bellaouar, Attia Nehar, Soumia Souffi, et al.*2025*

14 more papers of our library cite it; they have no page here yet.

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