Course Name: 

Sentiment Analysis (IT439)


B.Tech (AI)


Programme Specific Electives (PSE)

Credits (L-T-P): 

(3-0-2) 4


Introduction to Sentiment, Subjectivity, and Stance; Overview, From Words to Discourse & Pragmatics, From Text to Tweets to Speech, Joint Models, Recognizing Stances, Arguments, and Viewpoints, Lexicon-based approaches to sentiment analysis, Exploiting dictionaries, Ontologies, Specialized corpora for detecting the sentiment polarity in texts, Machine learning approaches to sentiment analysis, Sentiment and polarity detection as a classification problem. Neural network architectures for sentiment analysis, Neural network for sentiment detection and polarity evaluation, Affect and emotion detection in texts., Methods and techniques for modeling the language of emotions using neural networks and statistical language models., Exploitation of multimodal data in combination with text to detect the language of emotions, Applications and case studies.


Opinion mining and sentiment analysis, Bo Pang and Lillian Lee, Foundations and Trends in Information Retrieval 2(1-2), pp. 1-135, 2008.
Sentiment Analysis and Opinion Mining, Bing Liu, Morgan and Claypool Publishers, 2012.
Sentiment Analysis: Mining Opinions, Sentiments, and Emotions -Bing Liu , Cambridge University Press, 2015
Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition, 2nd edition, by Daniel Jurafsky and James Martin. (J&M)


Information Technology

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Head of the Department,
Department of Information Technology,
National Institute of Technology Karnataka,
SurathkalP. O. Srinivasnagar, Mangalore - 575 025
Ph.:    +91-824-2474056
Email:  hodit [at] nitk [dot] edu [dot] in

Web Admin: Sowmya Kamath S

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