---
title: "Who cites Subjectivity and Sentiment — 37 citing papers"
description: "37 papers of the Elamur Research library cite «Subjectivity and Sentiment Analysis of Modern Standard Arabic and Arabic Microblogs», found…"
canonical: "https://research.elamur.ai/free/en/papers/mourad-2013-subjectivity-sentiment-analysis-modern-standard/cited-by/"
---
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# Who cites «Subjectivity and Sentiment Analysis of Modern Standard Arabic and Arabic Microblogs»

37 papers of our library cite it (of the 149,439 whose bibliographies we read) · 33 with a page here, the most cited first · [← back to «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/)

1. **[SemEval-2017 Task 4: Sentiment Analysis in Twitter](https://md.research.elamur.ai/free/en/papers/rosenthal-2017-semeval-2017-task-4-sentiment/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Sara Rosenthal, Noura Farra, Preslav Nakov*2017 · 1,163 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. **[Sentiment after Translation: A Case-Study on Arabic Social Media Posts](https://md.research.elamur.ai/free/en/papers/salameh-2015-sentiment-after-translation-case-study/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Mohammad Salameh, Saif Mohammad, Svetlana Kiritchenko*2015 · 189 citations*
4. **[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*
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. **[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*
7. **[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*
8. **[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*
9. [**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/)
10. **[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*
11. **[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*
12. **[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*
13. **[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*
14. [**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/)
15. **[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*
16. [**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/)
17. **[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*
18. **[POS Tagging for Arabic Tweets](https://md.research.elamur.ai/free/en/papers/albogamy-2015-pos-tagging-arabic-tweets/) [Recent Advances in Natural Language Processing (RANLP)](https://md.research.elamur.ai/free/en/venues/ranlp/)**Fahad Albogamy, Allan Ramsay*2015 · 26 citations*
19. [**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/)
20. **[SMARTies: Sentiment Models for Arabic Target entities](https://md.research.elamur.ai/free/en/papers/farra-2017-smarties-sentiment-models-arabic-target/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Noura Farra, Kathy McKeown*2017 · 15 citations*
21. **[Syntax-Ignorant N-gram Embeddings for Sentiment Analysis of Arabic Dialects](https://md.research.elamur.ai/free/en/papers/mulki-2019-syntax-ignorant-n-gram-embeddings/) [Arabic Natural Language Processing Workshop (WANLP)](https://md.research.elamur.ai/free/en/venues/wanlp/)**Hala Mulki, Hatem Haddad, Mourad Gridach, et al.*2019 · 13 citations*
22. **[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*
23. [**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/)
24. **[Fast and Robust POS tagger for Arabic Tweets Using Agreement-based Bootstrapping](https://md.research.elamur.ai/free/en/papers/albogamy-2016-fast-robust-pos-tagger-arabic/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Fahad Albogamy, Allan Ramsay*2016 · 11 citations*
25. **[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*
26. **[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*
27. **[Towards POS Tagging for Arabic Tweets](https://md.research.elamur.ai/free/en/papers/albogamy-2015-pos-tagging-arabic-tweets-w15-4325/) [Workshop on Noisy User-generated Text](https://md.research.elamur.ai/free/en/venues/wnut/)**Fahad Albogamy, Allan Ramasy*2015 · 7 citations*
28. **[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*
29. **[Empirical Evaluation of Leveraging Named Entities for Arabic Sentiment Analysis](https://md.research.elamur.ai/free/en/papers/mulki-2019-empirical-evaluation-leveraging-named-entities/) [The International Arab Journal of Information Technology](https://md.research.elamur.ai/free/en/venues/the-international-arab-journal-of-information-technology/)**Hala Mulki, Hatem Haddad, Mourad Gridach, et al.*2019 · 6 citations*
30. **[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*
31. **[ONE: Toward ONE model, ONE algorithm, ONE corpus dedicated to sentiment analysis of Arabic/Arabizi and its dialects](https://md.research.elamur.ai/free/en/papers/guellil-2021-one-one-model-one-algorithm/) [Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis](https://md.research.elamur.ai/free/en/venues/wassa/)**Imane Guellil, Faical Azouaou, Fodil Benali, et al.*2021 · 5 citations*
32. **[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*
33. **[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*

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

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