most citedFeature Specific Sentiment Analysis for Product Reviews

81 citations · 171 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL201346 cited

Sentiment Analysis : A Literature Survey

Subhabrata Mukherjee, Pushpak Bhattacharyya

Our day-to-day life has always been influenced by what people think. Ideas and opinions of others have always affected our own opinions. The explosion of Web 2.0 has led to increas…

cs.IR201217 cited

TwiSent: A Multistage System for Analyzing Sentiment in Twitter

Subhabrata Mukherjee, Akshat Malu, A. R. Balamurali +1

In this paper, we present TwiSent, a sentiment analysis system for Twitter. Based on the topic searched, TwiSent collects tweets pertaining to it and categorizes them into the diff…

cs.IR201224 cited

WikiSent : Weakly Supervised Sentiment Analysis Through Extractive Summarization With Wikipedia

Subhabrata Mukherjee, Pushpak Bhattacharyya

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 ne…

cs.IR201281 cited

Feature Specific Sentiment Analysis for Product Reviews

Subhabrata Mukherjee, Pushpak Bhattacharyya

In this paper, we present a novel approach to identify feature specific expressions of opinion in product reviews with different features and mixed emotions. The objective is reali…

cs.IR20123 cited

Leveraging Sentiment to Compute Word Similarity

A. R. Balamurali, Subhabrata Mukherjee, Akshat Malu +1

In this paper, we introduce a new WordNet based similarity metric, SenSim, which incorporates sentiment content (i.e., degree of positive or negative sentiment) of the words being…