Comparison of Sentiment Analysis on Auto-Summarized Text & Original Text using various Summarization Techniques

Abstract

In today’s day & age Text Summarization and Sentiment Analysis add lot of value to businesses and other organizations. Sentiment Analysis can help a business get an idea about their product and gather meaningful feedback from customers. And auto-text summarization helps in articulating the important points from a large data-set, doing so can make the viewers/readers get a quicker idea about that data-set, this data-set can be a large document, a blog or an article. This paper presents a new method of combining the concepts of Sentiment Analysis and Auto-Text Summarization so that content-writers can enhance the quality of their manuscript. In this research work, certain observations have been made which can help in analyzing the polarity and subjectivity of the summarized text using various summarizers. Businesses and other organizations can use this technique to enhance their online content and intrigue viewers or readers by creating a better digital content ecosystem.