Mohammad is a Research Officer at the National
Research Council Canada (NRC). He received his Ph.D. in Computer
Science from the University of
Toronto. His research interests are in Computational
Linguistics and Natural
Language Processing, especially Lexical
Semantics. He develops computational models for sentiment analysis,
emotion detection, semantic distance, and lexical-semantic relations such
as word-pair antonymy. His team has developed a sentiment analysis system
which ranked first in recent SemEval shared tasks on the sentiment analysis
of tweets and on aspect-based sentiment analysis. His word-emotion association
resource, the NRC Emotion Lexicon,
is widely used for text analysis and information visualization. His recent
work on generating music from emotions in text has garnered widespread
media attention, including articles in Time,
arXiv Blog, PC
World, and Popular
Complete List of Publications
- Several word-emotion association lexicons (such as the NRC Emotion Lexicon), word-sentiment lexicons (such as the NRC Hashtag Sentiment Lexicon), and word-colour association lexicons are available here.
World, May 15, 2014: AI System Reads Novels, Writes Music for Them.
Science, May 14, 2014: Robot Reads Novels, Writes Songs about Them.
May 12, 2014: Researchers Train Computers to Manipulate Human Emotions with Art.
May 11, 2014: 'TransProse' Software Creates Musical Soundtracks from Books.
- TIME, May
7, 2014: This Is What Classic Novels Sound Like When a Computer Turns Them Into Piano Music.
March23, 2014: Algorithm Composes Music By Text Analyzing the World's Best Novels.
Physics arXiv Blog, March 20, 2014: The Music Composed By An Algorithm Analysing The World’s Best Novels.
Hammer, December 3, 2013: Are Your Emails Communicating a Lack of Confidence?
Hub, November 10, 2013: Algorithm Tracks Literary Emotion in Shakespeare, the Brothers Grimm.
Physics ArXiv, October 4, 2013: Data Mining Reveals the Emotional Differences in Emails Written by Men and Women.
October 4, 2013: Data Mining Reveals the Emotional Differences In Emails From Men and Women.
Physics ArXiv, October 1, 2013: Text Analyser Reveals Emotional Temperature of Novels and Fairy Tales.
October 1, 2013: Text Analyzer Reveals Emotional 'Temperature' of Novels and Fairy Tales
New Scientist, September 27: What your email style says about your personality
- Also in Times of India, MSN, Pharmacon, Galileo, Amic, and others
Article in MIT Technology Review, September 5, 2013: How Mechanical Turkers Crowdsourced a Huge Lexicon of Links Between Words and Emotion.
August 14, 2013: Main Tweet: Researchers Dig Into The Intersection of Politics and Twitter.
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Explore the interactive visualization for the NRC Word-Emotion Association Lexicon.
My N is Ten Million: Using Social Media to Track Emotion, Mental Health, and Measure Personality Across Entire Populations. Gregory J Park, Saif M Mohammad, and Johannes C Eichstaedt. A symposium at the International Convention of Psychological Science (ICPS), March 2015, Amsterdam, The Netherlands.
Sentiment Analysis of Social Media
Texts. Saif M. Mohammad and Xiaodan Zhu. Tutorial at the 2014
Conference on Empirical Methods on Natural Language Processing, October
2014, Doha, Qatar.
Presentation Video Proposal
Professional Community Involvement
I am serving as Publicity Chair for the 2015 meeting of the North American Association for Computational Linguistics (NAACL-2015). I am also the Area Chair for Sentiment and Opinion Mining.
The Words are Alive: Associations with Sentiment, Emotions, Colours, and Music. Invited talk at Language Technology Institute, Carnegie Mellon University,
September 2014, Pittsburgh, PA.
Sentiment, Emotion, Purpose, and Style in Electoral Tweets. Saif M. Mohammad, Svetlana Kiritchenko, Xiaodan Zhu, and Joel Martin. Information Processing and Management, in the press.
BibTeX AnnotatedData UnannotatedData
Emotional, Colourful, Musical!
Keynote speech at the ACL
2014 Workshop on Computational Approaches to Subjectivity, Sentiment,
and Social Media (WASSA), June 27, 2014, Baltimore, MD.
Professional Community Involvement
I am one of the organizers of SemEval-2015 Task 10 - Sentiment Analysis in Twitter. Of special interest to me is subtask E - Determining strength of association of Twitter terms with positive sentiment (or, degree of prior polarity). Task description, trial data, test data, and other details available here.
Sentiment Analysis of Short Informal Texts. Svetlana
Kiritchenko, Xiaodan Zhu and Saif Mohammad. Journal of Artificial
Intelligence Research, volume 50, pages 723-762, August 2014.
NRC-Canada-2014: Detecting Aspects and Sentiment in Customer
Reviews, Svetlana Kiritchenko, Xiaodan Zhu, Colin Cherry, and
Saif M. Mohammad. In Proceedings of the eighth international workshop on
Semantic Evaluation Exercises (SemEval-2014), August 2014, Dublin, Ireland.
Our team (NRC-Canada) ranked first
in three of the six subtasks. About 30 teams participated.
NRC-Canada-2014: Recent Improvements in Sentiment Analysis of
Tweets, Xiaodan Zhu, Svetlana Kiritchenko, and Saif M. Mohammad.
In Proceedings of the eighth international workshop on Semantic Evaluation
Exercises (SemEval-2014), August 2014, Dublin, Ireland.
Rankings: Our team (NRC-Canada) ranked first
in five of the ten subtask-domain combinations. About 40 teams participated.
An Empirical Study on the Effect of Negation Words on Sentiment.
Xiaodan Zhu, Hongyu Guo, Saif Mohammad and Svetlana Kiritchenko.
In Proceedings of the 52nd Annual Meeting of the Association for Computational
Linguistics, June 2014, Baltimore, MD.
Semantic Role Labeling of Emotions in Tweets. Saif M.
Mohammad, Xiaodan Zhu, and Joel Martin, In Proceedings of the ACL 2014
Workshop on Computational Approaches to Subjectivity, Sentiment, and Social
Media (WASSA), June 2014, Baltimore, MD.
Paper (pdf) BibTeX AnnotatedData UnannotatedData
Generating Music from Literature. Hannah Davis and Saif
M. Mohammad, In Proceedings of the EACL Workshop on Computational
Linguistics for Literature, April 2014, Gothenburg, Sweden.
Notable Press Mentions: The
Physics arXiv Blog, March 20, 2014, TIME,
May 7, 2014, PC
World, May 15, 2014, Popular
Science, May 14, 2014, io9,
May 12, 2014, LiveScience,
May 11, 2014.
Experiments with Three Approaches to Recognizing Lexical
Entailment. Peter D. Turney, Saif M. Mohammad, Natural Language
Engineering, in press.
Using Hashtags to Capture Fine Emotion Categories from Tweets.
Saif M. Mohammad, Svetlana Kiritchenko, Computational Intelligence, in
Paper (pdf) BibTeX
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