maoisdamao/mvsa

open research topic discussion

Movie Review Sentiment Analysis

By: @Pennsy

This project examines different text features for sentiment classifier on movie review data. The methods used for the classifier are Naïve Bayes, SVM with linear kernel and Logistic Regression. The features considered are unigrams with tf*idf, lemmatization, stop words and Part-of-Speech tagging.

Most of the work in the project refers the work done in (Bo, 2002). Besides reproduce their work, this study evaluates the effectiveness of Part-of-Speech tagging on polarity classification.

The movie review dataset used in this project is The Polarity Dataset (Bo, 2004).

Support Library

SpaCy

nltk

Scikit-learn

Reference

Bo Pang, Lillian Lee, and Shivakumar Vaithyanathan, Thumbs up? Sentiment Classification using Machine Learning Techniques, Proceedings of EMNLP 2002.

Bo Pang and Lillian Lee, A Sentimental Education: Sentiment Analysis Using Subjectivity Summarization Based on Minimum Cuts, Proceedings of ACL 2004.

mvsa's Issues

paper review on sentimental analysis

This issue is open for paper review update done on the topic sentimental analysis.