--- title: "Who cites Capturing Reliable Fine-Grained — 73 citing papers" description: "73 papers of the Elamur Research library cite «Capturing Reliable Fine-Grained Sentiment Associations by Crowdsourcing and Best–Worst…" canonical: "https://research.elamur.ai/free/en/papers/kiritchenko-2016-capturing-reliable-fine-grained-sentiment/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/kiritchenko-2016-capturing-reliable-fine-grained-sentiment/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Capturing Reliable Fine-Grained Sentiment…](https://md.research.elamur.ai/free/en/papers/kiritchenko-2016-capturing-reliable-fine-grained-sentiment/) / cited by # Who cites «Capturing Reliable Fine-Grained Sentiment Associations by Crowdsourcing and Best–Worst Scaling» 73 papers of our library cite it (of the 141,840 whose bibliographies we read) · 11 with a page here, the most cited first · [← back to «Capturing Reliable Fine-Grained Sentiment Associations by Crowdsourcing and Best–Worst Scaling»](https://md.research.elamur.ai/free/en/papers/kiritchenko-2016-capturing-reliable-fine-grained-sentiment/) 1. **[SemEval-2018 Task 1: Affect in Tweets](https://md.research.elamur.ai/free/en/papers/mohammad-2018-semeval-2018-task-1-affect/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Saif Mohammad, Felipe Bravo-Marquez, Mohammad Salameh, et al.*2018 · 1,094 citations* 2. **[Obtaining Reliable Human Ratings of Valence, Arousal, and Dominance for 20,000 English Words](https://md.research.elamur.ai/free/en/papers/mohammad-2018-obtaining-reliable-human-ratings-valence/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Saif Mohammad*2018 · 800 citations* 3. **[WASSA-2017 Shared Task on Emotion Intensity](https://md.research.elamur.ai/free/en/papers/mohammad-2017-wassa-2017-shared-task-emotion/) [Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis](https://md.research.elamur.ai/free/en/venues/wassa/)**Saif Mohammad, Felipe Bravo-Marquez*2017 · 369 citations* 4. **[Emotion Intensities in Tweets](https://md.research.elamur.ai/free/en/papers/mohammad-2017-emotion-intensities-tweets/) [Joint Conference on Lexical and Computational Semantics (*SEM)](https://md.research.elamur.ai/free/en/venues/starsem/)**Saif Mohammad, Felipe Bravo-Marquez*2017 · 290 citations* 5. **[Text Generation from Knowledge Graphs with Graph Transformers](https://md.research.elamur.ai/free/en/papers/kedziorski-2019-text-generation-knowledge-graphs-graph/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Rik Koncel-Kedziorski, Dhanush Bekal, Yi Luan, et al.*2019 · 286 citations* 6. **[Best-Worst Scaling More Reliable than Rating Scales: A Case Study on Sentiment Intensity Annotation](https://md.research.elamur.ai/free/en/papers/kiritchenko-2017-best-worst-scaling-more-reliable/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Svetlana Kiritchenko, Saif Mohammad*2017 · 282 citations* 7. **[Augmented SBERT: Data Augmentation Method for Improving Bi-Encoders for Pairwise Sentence Scoring Tasks](https://md.research.elamur.ai/free/en/papers/thakur-2021-augmented-sbert-data-augmentation-method/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Nandan Thakur, Nils Reimers, Johannes Daxenberger, et al.*2021 · 276 citations* 8. **[Unsupervised Opinion Summarization as Copycat-Review Generation](https://md.research.elamur.ai/free/en/papers/brazinskas-2020-unsupervised-opinion-summarization-as-copycat/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Arthur Bražinskas, Mirella Lapata, Ivan Titov*2020 · 173 citations* 9. **[Word Affect Intensities](https://md.research.elamur.ai/free/en/papers/mohammad-2018-word-affect-intensities/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Saif Mohammad*2018 · 114 citations* 10. [**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/) 11. **[Best-Worst Scaling of Hype in Biomedical Research: Building an Intensity Lexicon of Promotional Adjectives](https://md.research.elamur.ai/free/en/papers/millar-2026-best-worst-scaling-hype-biomedical/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Neil Millar, Dipesh Satav, Bojan Batalo, et al.*2026* 62 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/kiritchenko-2016-capturing-reliable-fine-grained-sentiment/) — Capturing Reliable Fine-Grained Sentiment Associations by Crowdsourcing and Best–Worst Scaling