A Machine Learning based Approach to Detect Sentiment in Twitter Data
Vivek Kumar Singh · INTERNATIONAL JOURNAL OF EMERGING TRENDS IN SCIENCE AND TECHNOLOGY · 2015
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 Naive Bayes classifier. First of all, the standard Naive Bayes classifier is implemented in R language and tested on two publicly available datasets comprising of sentiment labeled tweets. Then the standard Naive 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