A Machine Learning based Approach to Detect Sentiment in Twitter Data
Journal Title: International journal of Emerging Trends in Science and Technology - Year 2015, Vol 2, Issue 9
Abstract
This paper presents a machine learning based algorithmic approach to detect sentiment in Tweets posted by users on microblogging site Twitter. The experimental framework is based on use of a Naïve Bayes classifier. First of all, the standard Naïve Bayes classifier is implemented in R language and tested on two publicly available datasets comprising of sentiment labeled tweets. Then the standard Naïve Bayes classifier is modified to design a Lexicon-pooled hybrid classifier which incorporates knowledge from sentiment lexicon as well. The designs are evaluated for two feature selection schemes: tf and tf.idf. The accuracy of the different implementations is calculated and plotted diagrammatically. The proposed approach is a good and robust approach for detecting sentiment in tweets posted by users.
Authors and Affiliations
Vivek Kumar Singh
Keywords
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