|Saif M. Mohammad
Research Officer, National Research Council Canada
Recent News and Publications (2013 and later):
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 is garnering widespread
media attention, including articles in Time,
arXiv Blog, PC
World, and Popular
Notable Press Mentions:
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), 12-14 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.
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.
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.
NRC-Canada-2014: Detecting Aspects and Sentiment in Customer
Reviews, Svetlana Kiritchenko, Xiaodan Zhu, Colin Cherry, and
Saif M. Mohammad. In Proceedings of the eigth international workshop on
Semantic Evaluation Exercises (SemEval-2014), August 2014, Dublin, Ireland.
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 eigth international workshop on Semantic Evaluation
Exercises (SemEval-2014), August 2014, Dublin, Ireland.
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.
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.
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.
NRC-Canada: Building the State-of-the-Art in Sentiment Analysis
of Tweets, Saif M. Mohammad, Svetlana Kiritchenko, and Xiaodan
Zhu, In Proceedings of the seventh international workshop on Semantic
Evaluation Exercises (SemEval-2013), June 2013, Atlanta, USA.
Official Rankings: Our team (NRC-Canada) ranked first in detecting sentiment of tweets (task 2B - tweets), first in detecting sentiment of SMS messages (task 2B - SMS), first in detecting sentiment of terms within a tweet (task 2A - tweets), and second in detecting sentiment of terms within an SMS message (task 2A - SMS). About 44 teams participated.
Identifying Purpose Behind Electoral Tweets, Saif Mohammad,
Svetlana Kiritchenko and Joel Martin, In Proceedings of the KDD Workshop
on Issues of Sentiment Discovery and Opinion Mining (WISDOM-2013), August
2013, Chicago, USA.
Using Nuances of Emotion to Identify Personality, Saif
M. Mohammad and Svetlana Kiritchenko, In Proceedings of the ICWSM Workshop
on Computational Personality Recognition, July 2013, Boston, USA.
Generating Extractive Summaries of Scientific Paradigms,
Vahed Qazvinian, Dragomir R. Radev, Saif M. Mohammad, Bonnie Dorr, David
Zajic, Michael Whidby, Taesun Moon. Journal of Artificial Intelligence
Research (JAIR), 46, pages 165-201, 2013.
Last updated: November 2014.