---
title: "Who cites Julian Brooke — 335 papers of our library"
description: "335 papers of the Elamur Research library cite the works of Julian Brooke, found in their bibliographies; the most cited first."
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---
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# Who cites Julian Brooke

342 citations of their works from 335 papers of our library (of the 149,439 whose bibliographies we read) · 47 with a page here, the most cited first · [← Julian Brooke](https://md.research.elamur.ai/free/en/authors/julian-brooke/)

1. **[Tensor Fusion Network for Multimodal Sentiment Analysis](https://md.research.elamur.ai/free/en/papers/zadeh-2017-tensor-fusion-network-multimodal-sentiment/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Amir Zadeh, Minghai Chen, Soujanya Poria, et al.*2017 · 2,125 citations*
2. **[Learning Sentiment-Specific Word Embedding for Twitter Sentiment Classification](https://md.research.elamur.ai/free/en/papers/tang-2014-learning-sentiment-specific-word-embedding/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Duyu Tang, Furu Wei, Nan Yang, et al.*2014 · 1,346 citations*
3. **[Adaptive Recursive Neural Network for Target-dependent Twitter Sentiment Classification](https://md.research.elamur.ai/free/en/papers/dong-2014-adaptive-recursive-neural-network-target/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Li Dong, Furu Wei, Chuanqi Tan, et al.*2014 · 1,217 citations*
4. [**Dear Sir or Madam, May I Introduce the GYAFC Dataset: Corpus, Benchmarks and Metrics for Formality Style Transfer**Sudha Rao, Joel Tetreault*2018 · 582 citations*](https://md.research.elamur.ai/free/en/papers/rao-2018-dear-sir-or-madam-may/)
5. **[Who cares about Sarcastic Tweets? Investigating the Impact of Sarcasm on Sentiment Analysis.](https://md.research.elamur.ai/free/en/papers/maynard-2014-who-cares-about-sarcastic-tweets/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Diana Maynard, Mark Greenwood*2014 · 437 citations*
6. **[Inducing Domain-Specific Sentiment Lexicons from Unlabeled Corpora](https://md.research.elamur.ai/free/en/papers/hamilton-2016-inducing-domain-specific-sentiment-lexicons/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**William L. Hamilton, Kevin Clark, Jure Leskovec, et al.*2016 · 435 citations*
7. **[Knowledge-Enriched Transformer for Emotion Detection in Textual Conversations](https://md.research.elamur.ai/free/en/papers/zhong-2019-knowledge-enriched-transformer-emotion-detection/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Peixiang Zhong, Di Wang, Chunyan Miao*2019 · 373 citations*
8. **[SKEP: Sentiment Knowledge Enhanced Pre-training for Sentiment Analysis](https://md.research.elamur.ai/free/en/papers/tian-2020-skep-sentiment-knowledge-enhanced-pre/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hao Tian, Can Gao, Xinyan Xiao, et al.*2020 · 333 citations*
9. **[Developing Age and Gender Predictive Lexica over Social Media](https://md.research.elamur.ai/free/en/papers/sap-2014-developing-age-gender-predictive-lexica/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Maarten Sap, Gregory Park, Johannes Eichstaedt, et al.*2014 · 296 citations*
10. **[CODRA: A Novel Discriminative Framework for Rhetorical Analysis](https://md.research.elamur.ai/free/en/papers/joty-2015-codra-novel-discriminative-framework-rhetorical/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Shafiq Joty, Giuseppe Carenini, Raymond T. Ng*2015 · 263 citations*
11. **[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*
12. **[FUDGE: Controlled Text Generation With Future Discriminators](https://md.research.elamur.ai/free/en/papers/yang-2021-fudge-controlled-text-generation-future/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Kevin Yang, Dan Klein*2021 · 239 citations*
13. **[Arabic natural language processing: An overview](https://md.research.elamur.ai/free/en/papers/guellil-2019-arabic-natural-language-processing-overview/) [Journal of King Saud University - Computer and Information Sciences](https://md.research.elamur.ai/free/en/venues/journal-of-king-saud-university-computer-and-information-sciences/)**Imane Guellil, Houda Saadane, Faical Azouaou, et al.*2019 · 239 citations*
14. **[Better Document-level Sentiment Analysis from RST Discourse Parsing](https://md.research.elamur.ai/free/en/papers/bhatia-2015-better-document-level-sentiment-analysis/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Parminder Bhatia, Yangfeng Ji, Jacob Eisenstein*2015 · 235 citations*
15. **[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*
16. [**An Empirical Analysis of Formality in Online Communication**Ellie Pavlick, Joel Tetreault*2016 · 215 citations*](https://md.research.elamur.ai/free/en/papers/pavlick-2016-empirical-analysis-formality-online-communication/)
17. **[A Just and Comprehensive Strategy for Using NLP to Address Online Abuse](https://md.research.elamur.ai/free/en/papers/jurgens-2019-just-comprehensive-strategy-nlp-address/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**David Jurgens, Libby Hemphill, Eshwar Chandrasekharan*2019 · 189 citations*
18. **[Multiple Instance Learning Networks for Fine-Grained Sentiment Analysis](https://md.research.elamur.ai/free/en/papers/angelidis-2018-multiple-instance-learning-networks-fine/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Stefanos Angelidis, Mirella Lapata*2018 · 154 citations*
19. **[AfriSenti: A Twitter Sentiment Analysis Benchmark for African Languages](https://md.research.elamur.ai/free/en/papers/muhammad-2023-afrisenti-twitter-sentiment-analysis-benchmark/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Shamsuddeen Hassan Muhammad, Idris Abdulmumin, Abinew Ali Ayele, et al.*2023 · 143 citations*
20. **[Evaluative Language Beyond Bags of Words: Linguistic Insights and Computational Applications](https://md.research.elamur.ai/free/en/papers/benamara-2017-evaluative-language-beyond-bags-words/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Farah Benamara, Maite Taboada, Yannick Mathieu*2017 · 104 citations*
21. **[EMA at SemEval-2018 Task 1: Emotion Mining for Arabic](https://md.research.elamur.ai/free/en/papers/badaro-2018-ema-semeval-2018-task-1/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Gilbert Badaro, Obeida El Jundi, Alaa Khaddaj, et al.*2018 · 73 citations*
22. **[Detecting Disagreement in Conversations using Pseudo-Monologic Rhetorical Structure](https://md.research.elamur.ai/free/en/papers/allen-2014-detecting-disagreement-conversations-pseudo-monologic/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Kelsey Allen, Giuseppe Carenini, Raymond Ng*2014 · 60 citations*
23. [**SQUINKY! A Corpus of Sentence-level Formality, Informativeness, and Implicature arXiv:1506.02306**Shibamouli Lahiri*2015 · 44 citations*](https://md.research.elamur.ai/free/en/papers/lahiri-2015-squinky-corpus-sentence-level-formality/)
24. [**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/)
25. **[Frustrated, Polite, or Formal: Quantifying Feelings and Tone in Email](https://md.research.elamur.ai/free/en/papers/chhaya-2018-frustrated-polite-or-formal-quantifying/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Niyati Chhaya, Kushal Chawla, Tanya Goyal, et al.*2018 · 40 citations*
26. **[Arabizi sentiment analysis based on transliteration and automatic corpus annotation](https://md.research.elamur.ai/free/en/papers/guellil-2018-arabizi-sentiment-analysis-based-transliteration/) [Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis](https://md.research.elamur.ai/free/en/venues/wassa/)**Imane Guellil, Ahsan Adeel, Faical Azouaou, et al.*2018 · 35 citations*
27. **[A Dual-Channel Framework for Sarcasm Recognition by Detecting Sentiment Conflict](https://md.research.elamur.ai/free/en/papers/liu-2022-dual-channel-framework-sarcasm-recognition/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yiyi Liu, Yequan Wang, Aixin Sun, et al.*2022 · 34 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. **[BERT Knows Punta Cana is not just beautiful, it's gorgeous: Ranking Scalar Adjectives with Contextualised Representations](https://md.research.elamur.ai/free/en/papers/soler-2020-bert-knows-punta-cana-is/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Aina Garí Soler, Marianna Apidianaki*2020 · 30 citations*
32. [**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/)
33. **[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*
34. [**Learning Scalar Adjective Intensity from Paraphrases**Anne Cocos, Skyler Wharton, Ellie Pavlick, et al.*2018 · 21 citations*](https://md.research.elamur.ai/free/en/papers/cocos-2018-learning-scalar-adjective-intensity-paraphrases/)
35. [**Negation Handling in Machine Learning-Based Sentiment Classification for Colloquial Arabic arXiv:2107.11597 · International Journal of Operations Research and Information Systems (2020) 33-45**Omar Al-Harbi*2020 · 12 citations*](https://md.research.elamur.ai/free/en/papers/al-harbi-2021-negation-handling-machine-learning-based/)
36. [**SentiALG: Automated Corpus Annotation for Algerian Sentiment Analysis arXiv:1808.05079**Imane Guellil; Ahsan Adeel; Faical Azouaou;, Amir Hussain*2018 · 12 citations*](https://md.research.elamur.ai/free/en/papers/guellil-2018-sentialg-automated-corpus-annotation-algerian/)
37. [**Interpreting Verbal Irony: Linguistic Strategies and the Connection to the Type of Semantic Incongruity**Debanjan Ghosh, Elena Musi, Smaranda Muresan*2020 · 10 citations*](https://md.research.elamur.ai/free/en/papers/ghosh-2020-interpreting-verbal-irony-linguistic-strategies/)
38. **[Scalar Adjective Identification and Multilingual Ranking](https://md.research.elamur.ai/free/en/papers/soler-2021-scalar-adjective-identification-multilingual-ranking/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Aina Garí Soler, Marianna Apidianaki*2021 · 9 citations*
39. [**A Comprehensive View of the Biases of Toxicity and Sentiment Analysis Methods Towards Utterances with African American English Expressions arXiv:2401.12720**Guilherme H. Resende, Luiz F. Nery, Fabricio Benevenuto, et al.*2024 · 8 citations*](https://md.research.elamur.ai/free/en/papers/resende-2024-comprehensive-view-biases-toxicity-sentiment/)
40. **[Detecting Irony in Shakespeare's Sonnets with SPARSAR](https://md.research.elamur.ai/free/en/papers/delmonte-2019-detecting-irony-shakespeare-s-sonnets/) [Italian Conference on Computational Linguistics](https://md.research.elamur.ai/free/en/venues/clicit/)**Rodolfo Delmonte, Nicolò Busetto*2019 · 8 citations*
41. **[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*
42. [**Acquiring a Formality-Informed Lexical Resource for Style Analysis**Elisabeth Eder, Ulrike Krieg-Holz, Udo Hahn*2021 · 6 citations*](https://md.research.elamur.ai/free/en/papers/eder-2021-acquiring-formality-informed-lexical-resource/)
43. **[Sentiment Classification of Arabic Documents: Experiments with multi-type features and ensemble algorithms](https://md.research.elamur.ai/free/en/papers/bayoudhi-2015-sentiment-classification-arabic-documents-experiments/) [Pacific Asia Conference on Language, Information and Computation (PACLIC)](https://md.research.elamur.ai/free/en/venues/paclic/)**Amine Bayoudhi, Hatem Ghorbel, Lamia Hadrich Belguith*2015 · 6 citations*
44. **[LynyrdSkynyrd at WNUT-2020 Task 2: Semi-Supervised Learning for Identification of Informative COVID-19 English Tweets](https://md.research.elamur.ai/free/en/papers/sancheti-2020-lynyrdskynyrd-wnut-2020-task-2/) [Workshop on Noisy User-generated Text](https://md.research.elamur.ai/free/en/venues/wnut/)**Abhilasha Sancheti, Kushal Chawla, Gaurav Verma*2020 · 4 citations*
45. [**The Mechanical Bard: An Interpretable Machine Learning Approach to Shakespearean Sonnet Generation**Edwin Agnew, Michelle Qiu, Lily Zhu, et al.*2023 · 2 citations*](https://md.research.elamur.ai/free/en/papers/agnew-2023-mechanical-bard-interpretable-machine-learning/)
46. **[Neo-Classic: A Benchmark for Evaluating Linguistic-Aesthetic Reasoning in Classical Chinese Poetry](https://md.research.elamur.ai/free/en/papers/zhang-2026-neo-classic-benchmark-evaluating-linguistic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Han Zhang, Zihan Gu, Zhiyuan Wang, et al.*2026*
47. **[Scare Quotes as Markers of “Questionable” Word Usages and Misalignment in Conversation: An Annotation Study](https://md.research.elamur.ai/free/en/papers/soler-2026-scare-quotes-as-markers-questionable/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Aina Garí Soler, Juan Carlos Zevallos Huaco, Matthieu Labeau, et al.*2026*

288 more citing papers of our library have no page here yet.

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