Difference between revisions of "Wikisent: Weakly Supervised Sentiment Analysis Through Extractive Summarization with Wikipedia"

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'''Wikisent: Weakly Supervised Sentiment Analysis Through Extractive Summarization with Wikipedia''' - scientific work related to Wikipedia quality published in 2012, written by Subhabrata Mukherjee and Pushpak Bhattacharyya.
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'''Wikisent: Weakly Supervised Sentiment Analysis Through Extractive Summarization with Wikipedia''' - scientific work related to [[Wikipedia quality]] published in 2012, written by [[Subhabrata Mukherjee]] and [[Pushpak Bhattacharyya]].
  
 
== Overview ==
 
== Overview ==
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. Authors also perform a general movie review trend analysis using WikiSent.
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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. Authors also perform a general movie review trend analysis using WikiSent.

Revision as of 19:23, 10 March 2021

Wikisent: Weakly Supervised Sentiment Analysis Through Extractive Summarization with Wikipedia - scientific work related to Wikipedia quality published in 2012, written by Subhabrata Mukherjee and Pushpak Bhattacharyya.

Overview

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. Authors also perform a general movie review trend analysis using WikiSent.