DATS351 Sentiment Analysis (3 semester hours)
Sentiment analysis is a specialized form of natural language process intended to determine opinions expressed in written text. This is a lab-based course designed to implement topics covered in labs. The topics covered include the concepts and theories behind Sentiment Analysis. Discussion of the research approaches taken in Sentiment Analysis, knowledge-based techniques, statistical methods, supervised and unsupervised learning, and hybrid approaches. Tasks in Sentiment Analysis will be discussed and implemented through labs, e.g. classifying polarity, and determining an emotional scale. Students will learn how to generate a Sentiment Lexicon. (Prerequisites: MATH302, DATS411)
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