News media biasness detector

Abstract

This project looks into the field of web mining and artificial intelligence involving sentiment analysis. The purpose of this document is to provide a detail description of the project in all aspects so in this report we described everything about our project the main part of this report includes Introduction, Idea and Problem definition, Requirements gathering, Design and Implementations details and Testing details. The project describes the method in which news are scrapped through Web Scrapping in order to get real time data on the website. We have followed four different research papers to develop this system. We have merge, enhanced and optimized these techniques and algorithms which are described in the research papers. The goal of this project is to fetch news data on run time, analyze it and provide them with accurate news on the analyzed data from a news generating source of the current trends. Due to rapid growth of media content such as news and blogs that are available on internet there is need to design news biasness detector. It will help the user to access the neutral news article depending upon their interest from millions of resources, such as Sports, Business, Entertainment etc. Daily life of a person being busy and hectic gives no time to a person to search for the neutral news of their interest in a huge sea of internet. To reduce time, our system will be developed to provide an efficient and neutral news facility under one roof. The aspects being explored and learned are the core skills and techniques that are required to achieve the desired goal.