Efficient topic level opinion mining and sentiment analysis algorithm using latent dirichlet allocation model

Abstract

This paper discusses an efficient algorithm for topic level opinion mining and sentiment analysis of online text reviews by using unsupervised topic model, latent dirichlet allocation (LDA) for topic extraction and sentiment analysis of text reviews. The model accuracy is validated on twitter data by evaluating parameters perplexity and loglikelihood and compared with earlier models.