Author : Gaurav M Pai 1
Date of Publication :26th April 2018
Abstract: In this age, information is available in abundance on the internet, there are many platforms where news articles are published. It is nearly impossible to manually read articles from all the sources to understand the opinions of the authors. We require sentiment analysis systems to automatically detect sentiments of topics discussed by authors of these articles. Sentiment Analysis is the process of evaluating a piece of text to determine whether the expression is positive, negative or neutral in nature. In this paper, we present a system that performs Sentiment Analysis of topics which are discovered from a collection news articles using probabilistic topic modeling technique called Latent Dirichlet Allocation. We found that there was coherence between our results and the real-world scenarios that existed at the time of publication of the articles.
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