Text Summarization with Sentimental Analysis

Kummari Shiva Kumar , M Priyanka, M Rishitha, D Divya Teja, Nallamothu Madhuri

Abstract

In today’s world, Modern organizations deal with terabytes of text, such as email, that often plays a significant role in their day to day operations. The user has to face a task of identifying useful information from these data which is difficult and it requires some amount of time. One possible means is to use text summarization. Text summarization is the process of identifying the most valued/meaningful information in a document and compressing that information into a shorter version preserving its overall meaning. Sentiment analysis is about determining the text given by the user whether it is Positive, Negative or Neutral. We used Gensim Algorithm for generating text summary. This algorithm automatically summarizes the given text, by extracting one or more important sentences from the text. This project is about text summarization which includes sentiment analysis. In UI, a text box will be displayed, which is used to take the input text from the user which need to be summarize. Then it will pre-process the text and show the summarized content. It will be taking input as URL of an article and it is going to provide Title, Author, Publication Date, Sentimental analysis, Keywords, URL of an Article.