Text Summarization with Sentimental Analysis

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.