| NRC-Canada: Building the State-of-the-Art in Sentiment Analysis of Tweets SM Mohammad, S Kiritchenko, X Zhu 7th International Workshop on Semantic Evaluation Exercises (SemEval-2013), 2013 | 1359 | 2013 |
| Sentiment analysis of short informal texts S Kiritchenko, X Zhu, SM Mohammad Journal of Artificial Intelligence Research 50, 723-762, 2014 | 1135 | 2014 |
| Semeval-2016 task 6: Detecting stance in tweets S Mohammad, S Kiritchenko, P Sobhani, X Zhu, C Cherry Proceedings of the 10th international workshop on semantic evaluation …, 2016 | 1045 | 2016 |
| Semeval-2018 task 1: Affect in tweets S Mohammad, F Bravo-Marquez, M Salameh, S Kiritchenko Proceedings of the 12th international workshop on semantic evaluation, 1-17, 2018 | 920 | 2018 |
| NRC-Canada-2014: Detecting aspects and sentiment in customer reviews S Kiritchenko, X Zhu, C Cherry, S Mohammad Proceedings of the 8th international workshop on semantic evaluation …, 2014 | 869 | 2014 |
| Stance and sentiment in tweets SM Mohammad, P Sobhani, S Kiritchenko ACM Transactions on Internet Technology (TOIT) 17 (3), 1-23, 2017 | 609 | 2017 |
| Examining gender and race bias in two hundred sentiment analysis systems S Kiritchenko, SM Mohammad Proceedings of the 7th Joint Conference on Lexical and Computational …, 2018 | 513 | 2018 |
| Using hashtags to capture fine emotion categories from tweets SM Mohammad, S Kiritchenko Computational Intelligence 31 (2), 301-326, 2015 | 507 | 2015 |
| Email classification with co-training S Kiritchenko, S Matwin Proceedings of the 2001 Conference of the Center for Advanced Studies on …, 2001 | 335 | 2001 |
| Sentiment, emotion, purpose, and style in electoral tweets SM Mohammad, X Zhu, S Kiritchenko, J Martin Information Processing & Management 51 (4), 480-499, 2015 | 306 | 2015 |
| Machine-learned solutions for three stages of clinical information extraction: the state of the art at i2b2 2010 B De Bruijn, C Cherry, S Kiritchenko, J Martin, X Zhu Journal of the American Medical Informatics Association 18 (5), 557-562, 2011 | 294 | 2011 |
| How translation alters sentiment SM Mohammad, M Salameh, S Kiritchenko Journal of Artificial Intelligence Research 55, 95-130, 2016 | 235 | 2016 |
| Best-worst scaling more reliable than rating scales: A case study on sentiment intensity annotation S Kiritchenko, SM Mohammad Proceedings of the Annual Meeting of the Association for Computational …, 2017 | 212 | 2017 |
| Functional annotation of genes using hierarchical text categorization S Kiritchenko, S Matwin, F Famili BioLINK SIG: Linking Literature, Information and Knowledge for Biology, 2005 | 203 | 2005 |
| Sentiment after translation: A case-study on arabic social media posts M Salameh, S Mohammad, S Kiritchenko Proceedings of the 2015 conference of the North American chapter of the …, 2015 | 195 | 2015 |
| ExaCT: automatic extraction of clinical trial characteristics from journal publications S Kiritchenko, B De Bruijn, S Carini, J Martin, I Sim BMC medical informatics and decision making 10, 1-17, 2010 | 188 | 2010 |
| NRC-Canada-2014: Recent improvements in the sentiment analysis of tweets X Zhu, S Kiritchenko, S Mohammad Proceedings of the 8th international workshop on semantic evaluation …, 2014 | 162 | 2014 |
| Learning and evaluation in the presence of class hierarchies: application to text categorization S Kiritchenko, S Matwin, R Nock, F Famili 19th Canadian Conference on Artificial Intelligence, 395-406, 2006 | 158 | 2006 |
| A dataset for detecting stance in tweets S Mohammad, S Kiritchenko, P Sobhani, X Zhu, C Cherry Proceedings of the Tenth International Conference on Language Resources and …, 2016 | 152 | 2016 |
| Detecting stance in tweets and analyzing its interaction with sentiment P Sobhani, S Mohammad, S Kiritchenko Proceedings of the fifth joint conference on lexical and computational …, 2016 | 148 | 2016 |
Saif M. MohammadSenior Research Scientist (Emotions and Language, Affective Science, NLP), National Research CouncilVerified email at nrc-cnrc.gc.ca
