---
title: "National Research Council Canada — works"
description: "36 works by researchers of National Research Council Canada in our library, the most cited first."
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# Works of National Research Council Canada

36 works · the most cited first · [← National Research Council Canada](https://md.research.elamur.ai/free/en/government/national-research-council-canada/)

1. [**Thumbs Up or Thumbs Down? Semantic Orientation Applied to Unsupervised Classification of Reviews**Peter Turney*2002 · 2,826 citations*](https://md.research.elamur.ai/free/en/papers/turney-2002-thumbs-up-or-thumbs-down/)
2. [**SemEval-2016 Task 6: Detecting Stance in Tweets**Saif Mohammad, Svetlana Kiritchenko, Parinaz Sobhani, et al.*2016 · 1,196 citations*](https://md.research.elamur.ai/free/en/papers/mohammad-2016-semeval-2016-task-6-detecting/)
3. [**SemEval-2018 Task 1: Affect in Tweets**Saif Mohammad, Felipe Bravo-Marquez, Mohammad Salameh, et al.*2018 · 1,092 citations*](https://md.research.elamur.ai/free/en/papers/mohammad-2018-semeval-2018-task-1-affect/)
4. [**Emotions Evoked by Common Words and Phrases: Using Mechanical Turk to Create an Emotion Lexicon**Saif Mohammad, Peter Turney*2010 · 1,005 citations*](https://md.research.elamur.ai/free/en/papers/mohammad-2010-emotions-evoked-common-words-phrases/)
5. [**Obtaining Reliable Human Ratings of Valence, Arousal, and Dominance for 20,000 English Words**Saif Mohammad*2018 · 800 citations*](https://md.research.elamur.ai/free/en/papers/mohammad-2018-obtaining-reliable-human-ratings-valence/)
6. [**NRC-Canada-2014: Detecting Aspects and Sentiment in Customer Reviews**Svetlana Kiritchenko, Xiaodan Zhu, Colin Cherry, et al.*2014 · 788 citations*](https://md.research.elamur.ai/free/en/papers/kiritchenko-2014-nrc-canada-2014-detecting-aspects/)
7. [**Data-Driven Response Generation in Social Media**Alan Ritter, Colin Cherry, William B. Dolan*2011 · 692 citations*](https://md.research.elamur.ai/free/en/papers/ritter-2011-data-driven-response-generation-social/)
8. [**Findings of the 2017 Conference on Machine Translation (WMT17)**Ondřej Bojar, Rajen Chatterjee, Christian Federmann, et al.*2017 · 685 citations*](https://md.research.elamur.ai/free/en/papers/bojar-2017-findings-2017-conference-machine-translation/)
9. [**Examining Gender and Race Bias in Two Hundred Sentiment Analysis Systems**Svetlana Kiritchenko, Saif Mohammad*2018 · 574 citations*](https://md.research.elamur.ai/free/en/papers/kiritchenko-2018-examining-gender-race-bias-two/)
10. [**Unsupervised Modeling of Twitter Conversations**Alan Ritter, Colin Cherry, Bill Dolan*2010 · 557 citations*](https://md.research.elamur.ai/free/en/papers/ritter-2010-unsupervised-modeling-twitter-conversations/)
11. [**Batch Tuning Strategies for Statistical Machine Translation**Colin Cherry, George Foster*2012 · 548 citations*](https://md.research.elamur.ai/free/en/papers/cherry-2012-batch-tuning-strategies-statistical-machine/)
12. [**SemEval-2015 Task 10: Sentiment Analysis in Twitter**Sara Rosenthal, Preslav Nakov, Svetlana Kiritchenko, et al.*2015 · 490 citations*](https://md.research.elamur.ai/free/en/papers/rosenthal-2015-semeval-2015-task-10-sentiment/)
13. [**Findings of the 2020 Conference on Machine Translation (WMT20)**Loïc Barrault, Magdalena Biesialska, Ondřej Bojar, et al.*2020 · 401 citations*](https://md.research.elamur.ai/free/en/papers/barrault-2020-findings-2020-conference-machine-translation/)
14. [**Mixture-Model Adaptation for SMT**George Foster, Roland Kuhn*2007 · 397 citations*](https://md.research.elamur.ai/free/en/papers/foster-2007-mixture-model-adaptation-smt/)
15. [**Literal and Metaphorical Sense Identification through Concrete and Abstract Context**Peter Turney, Yair Neuman, Dan Assaf, et al.*2011 · 394 citations*](https://md.research.elamur.ai/free/en/papers/turney-2011-literal-metaphorical-sense-identification-through/)
16. [**WASSA-2017 Shared Task on Emotion Intensity**Saif Mohammad, Felipe Bravo-Marquez*2017 · 368 citations*](https://md.research.elamur.ai/free/en/papers/mohammad-2017-wassa-2017-shared-task-emotion/)
17. [**Arabic Preprocessing Schemes for Statistical Machine Translation**Nizar Habash, Fatiha Sadat*2006 · 358 citations*](https://md.research.elamur.ai/free/en/papers/habash-2006-arabic-preprocessing-schemes-statistical-machine/)
18. [**Choosing Transfer Languages for Cross-Lingual Learning**Yu-Hsiang Lin, Chian-Yu Chen, Jean Lee, et al.*2019 · 313 citations*](https://md.research.elamur.ai/free/en/papers/lin-2019-choosing-transfer-languages-cross-lingual/)
19. [**Discriminative Instance Weighting for Domain Adaptation in Statistical Machine Translation**George Foster, Cyril Goutte, Roland Kuhn*2010 · 305 citations*](https://md.research.elamur.ai/free/en/papers/foster-2010-discriminative-instance-weighting-domain-adaptation/)
20. [**Emotion Intensities in Tweets**Saif Mohammad, Felipe Bravo-Marquez*2017 · 290 citations*](https://md.research.elamur.ai/free/en/papers/mohammad-2017-emotion-intensities-tweets/)
21. [**Metaphor as a Medium for Emotion: An Empirical Study**Saif Mohammad, Ekaterina Shutova, Peter Turney*2016 · 285 citations*](https://md.research.elamur.ai/free/en/papers/mohammad-2016-metaphor-as-medium-emotion-empirical/)
22. [**Best-Worst Scaling More Reliable than Rating Scales: A Case Study on Sentiment Intensity Annotation**Svetlana Kiritchenko, Saif Mohammad*2017 · 282 citations*](https://md.research.elamur.ai/free/en/papers/kiritchenko-2017-best-worst-scaling-more-reliable/)
23. [**A Systematic Comparison of Smoothing Techniques for Sentence-Level BLEU**Boxing Chen, Colin Cherry*2014 · 281 citations*](https://md.research.elamur.ai/free/en/papers/chen-2014-systematic-comparison-smoothing-techniques-sentence/)
24. [**Similarity of Semantic Relations**Peter D. Turney*2006 · 277 citations*](https://md.research.elamur.ai/free/en/papers/turney-2006-similarity-semantic-relations/)
25. [**A Challenge Set Approach to Evaluating Machine Translation**Pierre Isabelle, Colin Cherry, George Foster*2017 · 269 citations*](https://md.research.elamur.ai/free/en/papers/isabelle-2017-challenge-set-approach-evaluating-machine/)
26. [**Results of WMT22 Metrics Shared Task: Stop Using BLEU – Neural Metrics Are Better and More Robust**Markus Freitag, Ricardo Rei, Nitika Mathur, et al.*2022 · 263 citations*](https://md.research.elamur.ai/free/en/papers/freitag-2022-results-wmt22-metrics-shared-task/)
27. [**Paraphrasing for Style**Wei Xu, Alan Ritter, Bill Dolan, et al.*2012 · 196 citations*](https://md.research.elamur.ai/free/en/papers/xu-2012-paraphrasing-style/)
28. [**A Dataset for Multi-Target Stance Detection**Parinaz Sobhani, Diana Inkpen, Xiaodan Zhu*2017 · 190 citations*](https://md.research.elamur.ai/free/en/papers/sobhani-2017-dataset-multi-target-stance-detection/)
29. [**Results of the WMT21 Metrics Shared Task: Evaluating Metrics with Expert-based Human Evaluations on TED and News Domain**Markus Freitag, Ricardo Rei, Nitika Mathur, et al.*2021 · 169 citations*](https://md.research.elamur.ai/free/en/papers/freitag-2021-results-wmt21-metrics-shared-task/)
30. [**Results of WMT23 Metrics Shared Task: Metrics Might Be Guilty but References Are Not Innocent**Markus Freitag, Nitika Mathur, Chi-kiu Lo, et al.*2023 · 155 citations*](https://md.research.elamur.ai/free/en/papers/freitag-2023-results-wmt23-metrics-shared-task/)
31. [**Word Affect Intensities**Saif Mohammad*2018 · 114 citations*](https://md.research.elamur.ai/free/en/papers/mohammad-2018-word-affect-intensities/)
32. [**Are LLMs Breaking MT Metrics? Results of the WMT24 Metrics Shared Task**Markus Freitag, Nitika Mathur, Daniel Deutsch, et al.*2024 · 106 citations*](https://md.research.elamur.ai/free/en/papers/freitag-2024-are-llms-breaking-mt-metrics/)
33. [**Measuring Machine Translation Errors in New Domains**Ann Irvine, John Morgan, Marine Carpuat, et al.*2013 · 104 citations*](https://md.research.elamur.ai/free/en/papers/irvine-2013-measuring-machine-translation-errors-new/)
34. [**MEANT 2.0: Accurate semantic MT evaluation for any output language**Chi-kiu Lo*2017 · 81 citations*](https://md.research.elamur.ai/free/en/papers/lo-2017-meant-2-0-accurate-semantic/)
35. [**Evaluating Emotion Arcs Across Languages: Bridging the Global Divide in Sentiment Analysis**Daniela Teodorescu, Saif Mohammad*2023 · 20 citations*](https://md.research.elamur.ai/free/en/papers/teodorescu-2023-evaluating-emotion-arcs-across-languages/)
36. [**Parser combinators for Tigrinya and Oromo morphology**Patrick Littell, Tom McCoy, Na-Rae Han, et al.*2018 · 2 citations*](https://md.research.elamur.ai/free/en/papers/littell-2018-parser-combinators-tigrinya-oromo-morphology/)
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