Sentiment Analysis PhD Seminar Balamurali A

Transcript:Sentiment Analysis PhD Seminar Balamurali A:
Sentiment Analysis PhD Seminar Balamurali A R(08405401) Under guidance of Prof. Pushpak Bhattacharyya Dept of CSE-IIT Bombay Mumbai Introduction Motivation Challenges General Model Word level sentiment analysis Sentence level sentiment analysis Comparative sentence analysis Document level sentiment analysis Conclusion & Future works References Outline Advent of UGC – A two way communication. Vast of information – Most of them direct feed backs Objective: To fine Sentiment or opinion of a user with regard to an entity/object Fine grain version of Subjectivity Analysis Subjectivity Analysis - finding whether phrase, sentence, document is subjective or objective. Sentiment Analysis(SA) - Introduction Businesses and organizations: Product and service benchmarking. Market intelligence. People: Finding opinions while purchasing a new product Finding opinions on political topics Advertisement: Placing ads in the user-generated content Place an ad when one praises a product. Place an ad from a competitor if one criticizes a product. Information search & Retrieval: Providing general search for "opinions". Motivation Opinion holder (source) :person who holds the sentiment. E.g. I love playing hockey. E.g I agree to what pope said “hate the sin not the sinners” - Object (Target) :product, person, organization or a topic on which sentiment is expressed. E.g. I like nano. But I don’t like the steering of nano. Opinion/sentiment a view or appraisal on an object E.g. It’s a pity(negative) that she didn’t marry. General Model Identifying source and target: some of the parts is in not equal to the whole- [Turney’02] Movies and the themes included – how to separate the sentiment “Movie was classic in fact Gabbar Singh was epitome of villainy!" Differentiating feature and attributes “I hate iPod, but I like the scroll technology” Role of semantics “How could anyone sit through this movie?” Issue of Ideology- [Sack’ 92] “Saddam Hussein” - Mixed opinion????? Challenges Sentiment Analysis: How to do? Word level Sentiment Analysis Used for grammatically incoherent text – Short news paper headlines e.g. Almost Perfection [The Hindu’22/04/09] Direct computation using lexical resource – SentiWordNet, WordNetAffect SentiWordNet – wordnet graded with pos(c),neg(c)& obj(c) score. e.g. Love Created using classifiers Interesting Findings -Mostly opinionated content carried by modifiers(adjective & adverbs) e.g. smart IITian source:http://sentiwordnet.isti.cnr.it E.g. “Manmohan insists troop stay in Guwhati, predicts midterm victory” System achieves valence accuracy of 55% UPAR’07 Contextual information necessary for SA at sentence level “Indian observers were not happy about things happening in its border country, even though west were enjoying the