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Erschienen in:
2012 | OriginalPaper | Buchkapitel
WikiSent: Weakly Supervised Sentiment Analysis through Extractive Summarization with Wikipedia
verfasst von : Subhabrata Mukherjee, Pushpak Bhattacharyya
Erschienen in: Machine Learning and Knowledge Discovery in Databases
Verlag: Springer Berlin Heidelberg
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This paper describes a
weakly
supervised system for sentiment analysis in the movie review domain. The objective is to classify a movie review into a polarity class,
positive
or
negative
, based on those sentences bearing opinion on the movie alone, leaving out other irrelevant text.
Wikipedia
incorporates the world knowledge of
movie-specific features
in the system which is used to obtain an
extractive summary
of the review, consisting of the reviewer’s opinions about the specific aspects of the movie. This filters out the concepts which are irrelevant or objective with respect to the given movie. The proposed system,
WikiSent
, does not require any labeled data for training. It achieves a better or comparable accuracy to the existing semi-supervised and unsupervised systems in the domain, on the same dataset. We also perform a general movie review
trend analysis
using WikiSent.