Bio

Dr. Saif Mohammad is Senior 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, Sentiment Analysis, Social Media Analytics, and Information Visualization. His team has developed a sentiment analysis system which ranked first in recent shared task competitions. His word-emotion association resource, the NRC Emotion Lexicon, is widely used for text analysis and information visualization. His work on detecting emotions in social media and on generating music from text have garnered widespread media attention, including articles in Time, SlashDot, LiveScience, io9, The Physics arXiv Blog, PC World, and Popular Science.

Complete List of Publications

• Publications grouped by area
• Publications ordered by date (Google Scholar page)
• Publication ordered by number of citations (Google Scholar page)

Data

• 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.

Notable Press Mentions

• Washington Post, October 22, 2016. Donald Trump and Hillary Clinton took to the debate stage and made sweet, sweet music. The article mentions NRC in relation to the lexicons we created, which were used to generate music from the Trump-Hillary debate text.
  
  
• Washington Post, CBS News, Columbia Tribune, and others, September 23, 2016. This symphony had both human and computer composers. Articles about a symphony orchestra performed music composed using the NRC Emotion Lexicon under the glass of the Louvre museum in Paris on Sept. 20, 2016. Click here for a video of the performance.
  
  
• Washington Post, August 12, 2016. Two people write Trump’s tweets. He writes the angrier ones.
  
  
• BGR, August 11, 2016. Donald Trump’s angriest tweets are sent from his Android while the nice ones are sent from an iPhone.
  
  
• NYC Data Science Academy, August 7, 2016. Twitter Analysis of Presidential Candidates 2016.
  
  
• Variance Explained, August 6, 2016. Text analysis of Trump's tweets confirms he writes only the (angrier) Android half.
  • News also picked up by NPR, Los Angeles Times, Scientific American, The Verge, and others.
    
    
• The Telegraph, June 15, 2016: EU referendum: Remain uses Project Fear more in tweets than Leave, analysis shows. [Use of the NRC Emotion Lexicon, aka EmoLex, to track sentiment in EU referendum tweets (Brexit).]
  
  
• An art project, the Wishing Wall, that uses the NRC Emotion lexicon was displayed in:
  • Tekniska Museet, Stockholm, Sweden (Oct 14 – Aug 15)
  • Onassis Cultural Centre, Athens (19th Oct’15 – 10th Jan’16)
  • Zorlu Centre in Istanbul (16th Feb – 12th June’16) 
     
• Fast Company, March 25, 2016: An Emotional Map Of The City, As Captured Through Its Sounds. [Use of the NRC Emotion Lexicon, aka EmoLex to create Chatty Maps.]
  
  
• Press release stating the use of EmoLex to create Chatty Maps.
  
  
• PC World, May 15, 2014: AI System Reads Novels, Writes Music for Them.
  
  
• Popular Science, May 14, 2014: Robot Reads Novels, Writes Songs about Them.
  
  
• io9, May 12, 2014: Researchers Train Computers to Manipulate Human Emotions with Art.
  
  
• LiveScience, 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.
  
  
• SlashDot, March23, 2014: Algorithm Composes Music By Text Analyzing the World's Best Novels.
  
  
• The Physics arXiv Blog, March 20, 2014: The Music Composed By An Algorithm Analysing The World’s Best Novels.
  
  
• Glass Hammer, December 3, 2013: Are Your Emails Communicating a Lack of Confidence?
  
  
• Singularity Hub, November 10, 2013: Algorithm Tracks Literary Emotion in Shakespeare, the Brothers Grimm.
  
  
• The Physics ArXiv, October 4, 2013: Data Mining Reveals the Emotional Differences in Emails Written by Men and Women.
  
  
• SlashDot, October 4, 2013: Data Mining Reveals the Emotional Differences In Emails From Men and Women.
  
  
• The Physics ArXiv, October 1, 2013: Text Analyser Reveals Emotional Temperature of Novels and Fairy Tales.
  • Also in EduBits
    
    
• SlashDot, October 1, 2013: Text Analyzer Reveals Emotional 'Temperature' of Novels and Fairy Tales
  
  
• The 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.
  • Also in its Spanish website and in crowdsourcing.org.
    
    
• TIME, August 14, 2013: Main Tweet: Researchers Dig Into The Intersection of Politics and Twitter.

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Invited Talks

Affect Associations in Creative Language. Keynote speech at the COLING 2016 workshop on Computational Modeling of People's Opinions, Personality, and Emotions in Social Media (PEOPLES 2016), December 12, 2016, Osaka, Japan.
Presentation

Affect Associations: The Building Blocks of Sentiment Analysis. Keynote speech at the 20th International Conference on Asian Language Processing (IALP 2016), November 21-23, 2016, National Cheng Kung University, Tainan, Taiwan.
Presentation

Affect Associations in Creative Language. Keynote speech at the 2016 IR Workshop at the Academia Sinica, November 24, 2016, Taipei, Taiwan.
Presentation

Capturing Reliable Fine-Grained Sentiment Associations by Crowdsourcing and Best–Worst Scaling. Invited talk at the TAMALE seminar series, September 15, 2016, University of Ottawa. (Joint work with, and talk given by, Svetlana Kiritchenko.)
Presentation

Metaphor as a Medium for Emotion: An Empirical Study. Invited talk at the TAMALE seminar series, September 15, 2016, University of Ottawa. (Joint work with Ekaterina Shutova and Peter Turney.)
Presentation

Professional Community Involvement

Co-chair for SemEval-2017 and SemEval-2018.

Co-organizer of the 8th Workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis (WASSA-2017), to be held in conjunction with EMNLP-2017, Copenhagen, Denmark.

Area chair for Sentiment Analysis and Opinion Mining at EMNLP-2018.

Event

A symphony orchestra performed music composed using the NRC Emotion Lexicon under the glass of the Louvre museum in Paris on Sept. 20, 2016. Click here for a video of the performance.
Artcles published in the Washington Post, CBS News, Columbia Tribune, and others.

Journal Paper

Stance and Sentiment in Tweets. Saif M. Mohammad, Parinaz Sobhani, and Svetlana Kiritchenko. Special Section of the ACM Transactions on Internet Technology on Argumentation in Social Media, In Press.
Paper (pdf)    BibTeX       Data and Visualization

Papers

Metaphor as a Medium for Emotion: An Empirical Study. Saif M. Mohammad, Ekaterina Shutova, and Peter Turney. In Proceedings of the Joint Conference on Lexical and Computational Semantics (*Sem), August 2016, Berlin, Germany.
Paper (pdf)    BibTeX     Presentation       Data and Interactive Visualization

Detecting Stance in Tweets And Analyzing its Interaction with Sentiment. Parinaz Sobhani, Saif M. Mohammad, and Svetlana Kiritchenko. In Proceedings of the Joint Conference on Lexical and Computational Semantics (*Sem), August 2016, Berlin, Germany.
Paper (pdf)    BibTeX    Presentation       Data and Visualization

Determining Word-Emotion Associations from Tweets by Multi-Label Classification. Felipe Bravo-Marquez, Eibe Frank, Saif Mohammad, and Bernhard Pfahringer. In Proceedings of the 2016 IEEE/WIC/ACM International Conference on Web Intelligence (WI'16), Omaha, Nebraska, USA.
Paper (pdf)    BibTeX    Data (scroll to section on this paper)

Invited Talk

Sentiment and Emotions in Tweets. Department of Geography & Geoinformation Science at George Mason University. May 29, 2016, FairFax, Virginia.
Presentation

Professional Community Involvement

Publicity Chair for the 2016 meeting of the 2016 Conference on Empirical Methods on Natural Language Processing. (EMNLP-2016).

Area Chair for Sentiment and Opinion Mining at EMNLP 2016.

Book Chapter

Challenges in Sentiment Analysis. Saif M. Mohammad, A Practical Guide to Sentiment Analysis, Springer, 2016.
Pre-print version (pdf)    BibTeX

Papers

Capturing Reliable Fine-Grained Sentiment Associations by Crowdsourcing and Best-Worst Scaling. Svetlana Kiritchenko and Saif M. Mohammad. In Proceedings of the 15th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. June 2016. San Diego, CA.
Paper (pdf)    BibTeX    Presentation     Data   

Sentiment Composition of Words with Opposing Polarities. Svetlana Kiritchenko and Saif M. Mohammad. In Proceedings of the 15th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. June 2016. San Diego, CA.
Paper (pdf)    BibTeX    Poster     Data: Opposing Polarity Sentiment Lexicon    Interactive Visualization

Semeval-2016 Task 6: Detecting Stance in Tweets. Saif M. Mohammad, Svetlana Kiritchenko, Parinaz Sobhani, Xiaodan Zhu, and Colin Cherry. In Proceedings of the International Workshop on Semantic Evaluation (SemEval ’16). June 2016. San Diego, California.
Paper (pdf)    BibTeX    Presentation    Task Website

Semeval-2016 Task 7: Determining Sentiment Intensity of English and Arabic Phrases. Svetlana Kiritchenko, Saif M. Mohammad, and Mohammad Salameh. In Proceedings of the International Workshop on Semantic Evaluation (SemEval ’16). June 2016. San Diego, California.
Paper (pdf)    BibTeX    Presentation    Task Website

A Practical Guide to Sentiment Annotation: Challenges and Solutions. Saif M. Mohammad, In Proceedings of the NAACL 2016 Workshop on Computational Approaches to Subjectivity, Sentiment, and Social Media (WASSA), June 2014, San Diego, California.
Paper (pdf)    BibTeX    Presentation    

The Effect of Negators, Modals, and Degree Adverbs on Sentiment Composition. Svetlana Kiritchenko and Saif M. Mohammad, In Proceedings of the NAACL 2016 Workshop on Computational Approaches to Subjectivity, Sentiment, and Social Media (WASSA), June 2014, San Diego, California.
Paper (pdf)    BibTeX    Presentation     Data (Sentiment Composition Lexicon of Negators, Modals, and Adverbs (SCL-NMA)) and Visualization

Sentiment Lexicons for Arabic Social Media. Saif M. Mohammad, Mohammad Salameh, and Svetlana Kiritchenko. In Proceedings of the 10th edition of the Language Resources and Evaluation Conference, May 2016, Portorož (Slovenia).
Paper (pdf)    BibTeX    Presentation       Data: Arabic Sentiment Lexicons

A Dataset for Detecting Stance in Tweets. Saif M. Mohammad, Svetlana Kiritchenko, Parinaz Sobhani, Xiaodan Zhu, and Colin Cherry. In Proceedings of the 10th edition of the Language Resources and Evaluation Conference, May 2016, Portorož (Slovenia).
Paper (pdf)    BibTeX    Presentation     Data: Stance Dataset    Interactive Visualization

Happy Accident: A Sentiment Lexicon of Opposing Polarities Phrases. Svetlana Kiritchenko and Saif M. Mohammad. In Proceedings of the 10th edition of the Language Resources and Evaluation Conference, May 2016, Portorož (Slovenia).
Paper (pdf)    BibTeX    Poster    Data: Opposing Polarity Sentiment Lexicon    Interactive Visualization

Book Chapter

Sentiment Analysis: Detecting Valence, Emotions, and Other Affectual States from Text. Saif M. Mohammad, Emotion Measurement, 2016.
Pre-print version (pdf)    BibTeX
This is a survey on automatic methods for affect analysis.

Interactive Visualization and Paper

Imagisaurus: An Interactive Visualizer of Valence and Emotion in the Roget’s Thesaurus. Saif M. Mohammad. In Proceedings of the EMNLP 2015 Workshop on Computational Approaches to Subjectivity, Sentiment, and Social Media (WASSA), September 2015, Lisbon, Portugal.
Paper (pdf)    BibTeX    Interactive Visualization

Data

The NRC Emotion Lexicon is now available in over 20 languages.

Journal Paper

How Translation Alters Sentiment. Saif M. Mohammad, Mohammad Salameh, and Svetlana Kiritchenko, Journal of Artificial Intelligence Research, 2016, Volume 55, pages 95-130.
Paper (pdf)    BibTeX    Data: Arabic Sentiment Lexicons

Professional Community Involvement

Organizing these shared task competitions under the aegis of SemEval-2016 (see webpage for schedule):

• Detecting Stance in Tweets (new task). Saif M. Mohammad, Svetlana Kiritchenko, Parinaz Sobhani, Xiaodan Zhu, and Colin Cherry.
• Determining sentiment intensity of English and Arabic phrases. Svetlana Kiritchenko, Saif M Mohammad, and Mohammad Salameh. This is an expansion of the SemEval-2015 Task 10 subtask E - Determining strength of association of Twitter terms with positive sentiment (or, degree of prior polarity).

Journal Paper

Developing a Successful SemEval Task in Sentiment Analysis of Twitter and Other Social Media Texts.Preslav Nakov, Sara Rosenthal, Svetlana Kiritchenko, Saif M. Mohammad, Zornitsa Kozareva, Alan Ritter, Veselin Stoyanov, and Xiaodan Zhu. Language Resources and Evaluation. March 2016, Volume 50, Issue 1, pages 35-65.
Paper (pdf)    Preprint Version (pdf)    BibTeX

Tutorial

Computational Analysis of Affect and Emotion in Language. Saif M. Mohammad and Cecilia Ovesdotter Alm. Tutorial at the 2015 Conference on Empirical Methods on Natural Language Processing, September 2015, Lisboa, Portugal.
Presentation       Annotated Bibliography       Extended Bibliography      Proposal

Papers

SemEval-2015 Task 10: Sentiment Analysis in Twitter. Sara Rosenthal, Preslav Nakov, Svetlana Kiritchenko, Saif M Mohammad, Alan Ritter, and Veselin Stoyanov. In Proceedings of the ninth international workshop on Semantic Evaluation Exercises (SemEval-2015), June 2015, Denver, Colorado.
Paper (pdf)    BibTeX

Sentiment After Translation: A Case-Study on Arabic Social Media Posts. Mohammad Salameh, Saif M Mohammad and Svetlana Kiritchenko, In Proceedings of the North American Chapter of the Association for Computational Linguistics (NAACL-2015), June 2015, Denver, Colorado.
Paper (pdf)    BibTeX   Data: rabic Sentiment Lexicons

Visualization

Explore the interactive visualization for the NRC Word-Emotion Association Lexicon.

Symposium

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.

Tutorial

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.

Invited Talk

The Words are Alive: Associations with Sentiment, Emotions, Colours, and Music. Invited talk at Language Technology Institute, Carnegie Mellon University, September 2014, Pittsburgh, PA.
Presentation    Video

Journal Paper

Sentiment, Emotion, Purpose, and Style in Electoral Tweets. Saif M. Mohammad, Svetlana Kiritchenko, Xiaodan Zhu, and Joel Martin. Information Processing and Management, Volume 51, Issue 4, July 2015, Pages 480–499.
Paper (pdf)    BibTeX     AnnotatedData    UnannotatedData

Invited Talk

Words: Evaluative, 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.
Presentation

Professional Community Involvement

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.

Journal Paper

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.
Paper (pdf)    BibTeX

Papers

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.
Paper (pdf)    BibTeX     Poster

Official Rankings: 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.
Paper (pdf)    BibTeX     Poster

Official 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.
Paper (pdf)    BibTeX

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.
Paper (pdf)    BibTeX    TransProse Website

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.

Journal Papers

Experiments with Three Approaches to Recognizing Lexical Entailment. Peter D. Turney, Saif M. Mohammad, Natural Language Engineering, Volume 21, Issue 3, May 2015.
Paper (pdf)    BibTeX

Using Hashtags to Capture Fine Emotion Categories from Tweets. Saif M. Mohammad, Svetlana Kiritchenko, Computational Intelligence, Volume 31, Issue 2, Pages 301-326, May 2015.
Paper (pdf)    BibTeX

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