Saif M. Mohammad

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Svetlana KiritchenkoNational Research Council CanadaEmail verificata su nrc-cnrc.gc.ca
Xiaodan ZhuECE & Ingenuity Labs Research Institute, Queen's University, CanadaEmail verificata su queensu.ca
Peter TurneyApperceptual.comEmail verificata su apperceptual.com
Graeme HirstProfessor of Computer Science, University of TorontoEmail verificata su cs.toronto.edu
Bonnie DorrUniversity of Florida, IHMC, UMDEmail verificata su ufl.edu
Felipe Bravo-MarquezAssociate Professor, University of ChileEmail verificata su dcc.uchile.cl
Mohammad SalamehPrincipal Researcher, Huawei TechnologiesEmail verificata su ualberta.ca
Colin CherryGoogle ResearchEmail verificata su google.com
Parinaz SobhaniEmail verificata su uottawa.ca
Preslav NakovMBZUAIEmail verificata su mbzuai.ac.ae
Sara RosenthalIBM ResearchEmail verificata su cs.columbia.edu
Ekaterina ShutovaILLC, University of AmsterdamEmail verificata su berkeley.edu
Krishnapriya VishnubhotlaUniversity of TorontoEmail verificata su cs.toronto.edu
Joel MartinNational Research CouncilEmail verificata su nrc-cnrc.gc.ca
Mohamed AbdallaUniversity of AlbertaEmail verificata su ualberta.ca
Jan Philip WahleUniversity of Göttingen (Prev: NRC Canada)Email verificata su uni-goettingen.de
Terry RuasUniversity of Göttingen (Prev: Uni. of Michigan, NII Tokyo, Uni. of Wuppertal, UFABC)Email verificata su uni-goettingen.de
Vahed QazvinianPraisidio; Google; University of Michigan, Ann ArborEmail verificata su google.com
Dragomir RadevProfessor, Computer Science, Yale UniversityEmail verificata su yale.edu
Berry de BruijnNational Research CouncilEmail verificata su nrc-cnrc.gc.ca

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Saif M. Mohammad

Principal Research Scientist (NLP,Computational Affective Science), National Research Council Canada

Email verificata su nrc-cnrc.gc.ca - Home page

Natural Language Processing Lexical Semantics Affective Science Emotion Recognition Sentiment


Titolo Ordina per citazioni Ordina per anno Ordina per titolo	Citata da Citata da	Anno
Crowdsourcing a word–emotion association lexicon SM Mohammad, PD Turney Computational intelligence 29 (3), 436-465, 2013	2993	2013
SemEval-2015 Task 10: Sentiment Analysis in Twitter VS Sara Rosenthal, Preslav Nakov, Svetlana Kiritchenko, Saif M. Mohammad ... arXiv:1912.02387, https://www.aclweb.org/anthology/S15-207, 2015	1853*	2015
Emotions evoked by common words and phrases: Using mechanical turk to create an emotion lexicon S Mohammad, P Turney Proceedings of the NAACL HLT 2010 workshop on computational approaches to …, 2010	1391	2010
NRC-Canada: Building the State-of-the-Art in Sentiment Analysis of Tweets SM Mohammad, S Kiritchenko, X Zhu SemEval-2013, 2013	1367	2013
Sentiment analysis of short informal texts S Kiritchenko, X Zhu, SM Mohammad Journal of Artificial Intelligence Research 50, 723-762, 2014	1146	2014
Beyond the imitation game: Quantifying and extrapolating the capabilities of language models A Srivastava, A Rastogi, A Rao, AAM Shoeb, A Abid, A Fisch, AR Brown, ... arXiv preprint arXiv:2206.04615, 2022	1140	2022
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	1069	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	942	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	876	2014
Obtaining reliable human ratings of valence, arousal, and dominance for 20,000 English words S Mohammad Proceedings of the 56th annual meeting of the association for computational …, 2018	710	2018
Stance and sentiment in tweets SM Mohammad, P Sobhani, S Kiritchenko ACM Transactions on Internet Technology (TOIT) 17 (3), 1-23, 2017	618	2017
Sentiment analysis: Detecting valence, emotions, and other affectual states from text SM Mohammad Emotion measurement, 201-237, 2016	608	2016
Examining gender and race bias in two hundred sentiment analysis systems S Kiritchenko, SM Mohammad arXiv preprint arXiv:1805.04508, 2018	536	2018
Using hashtags to capture fine emotion categories from tweets SM Mohammad, S Kiritchenko Computational Intelligence 31 (2), 301-326, 2015	514	2015
NRC Emotion Lexicon SM Mohammad, PD Turney National Research Council, Canada 2, 2013	491	2013
From once upon a time to happily ever after: Tracking emotions in mail and books SM Mohammad Decision Support Systems 53 (4), 730-741, 2012	457	2012
Word affect intensities SM Mohammad arXiv preprint arXiv:1704.08798, 2017	451	2017
Generating high-coverage semantic orientation lexicons from overtly marked words and a thesaurus S Mohammad, C Dunne, B Dorr Proceedings of the 2009 conference on empirical methods in natural language …, 2009	333	2009
WASSA-2017 shared task on emotion intensity SM Mohammad, F Bravo-Marquez arXiv preprint arXiv:1708.03700, 2017	328	2017
#Emotional Tweets SM Mohammad StarSem, 2012	328	2012

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