Dr. Saif Mohammad (NRC-Canada) will deliver the 2017-2018 Distinguished Computational Linguistics Lecture in the GOL Auditorium, followed by a reception in the GOL Atrium. Sponsor/co-sponsor: Language Science, CLaSP, and the GCCIS PhD Program.
The Search for Emotions in Language
Dr. Saif M. Mohammad, Senior Research Scientist, National Research Council Canada
Emotions are central to human experience and behavior. They are crucial for organizing meaning and reasoning about the world we live in. They are ubiquitous and everyday, yet their secrets remain elusive. In this talk, I will describe our work on the search for emotions in language – by humans and by machines.
I will describe large crowdsourced studies asking people to detect emotions associated with words, phrases, sentences, and tweets. I will flesh out the various ways in which emotions can be represented, challenges in obtaining reliable annotations, and approaches that address these problems. The emotion lexicons thus created, with entries for tens of thousands of English terms, have wide-ranging applications in natural language processing, psychology, social sciences, digital humanities, and data sonification. I will highlight some of the applications we have explored in literary analysis and automatic text-based music generation. The human annotations also shed light on compelling research questions involving how we organize meaning, the fine-grained distinctions we make, our shared understanding of the world, and the extent to which differences in gender, age, and personality impact this shared understanding.
In the second part of my talk, I will present supervised machine learning methods for detecting emotions associated with text. This will include our NRC-Canada system that stood first in three SemEval-2013 and SemEval-2014 sentiment analysis shared task competitions. Next, I will flesh out shared tasks that we have organized 2015 through 2018 that go beyond traditional sentiment classification. These include inferring stance from tweets that may or may not explicitly mention the target of interest and detecting fine-grained emotion intensity. Finally, I will conclude with ongoing work on assessing the degree of inappropriate biases in automatic emotion systems.
Acknowledgments: This talk includes joint work with a number of researchers and graduate students, with substantial contributions from Svetlana Kiritchenko and Peter Turney.
Dr. Saif M. Mohammad is Senior Research Scientist at the National Research Council Canada (NRC). He received his Ph.D. in Computer Science from the University of Toronto. Before joining NRC, Saif was a Research Associate at the Institute of Advanced Computer Studies at the University of Maryland, College Park. His research interests are in Computational Linguistics, especially Lexical Semantics, Crowdsourced Human Annotations, Sentiment Analysis, Social Media Analysis, and Information Visualization. He has served as the area chair for Sentiment Analysis in past ACL conferences. Saif is a co-organizer of WASSA (a sentiment analysis workshop) and co-chair of SemEval (the largest shared task platform for NLP tasks). His work on detecting emotions in social media and on generating music from text have garnered media attention, including articles in Time, Slashdot, LiveScience, io9, The Physics arXiv Blog, PC World, and Popular Science. Webpage: http://saifmohammad.com