Efficient daily news platform generation using natural language processing

Abstract

In today’s digital world, online journalism plays a vital role across various facets of humanity, starting from day-to-day lives, to the extent of deciding presidential elections. Moreover, with the growth in popularity of automation in every possible field known to humans, automated journalism is an important domain to research into. In this, there are many factors that come into play such as relative importance of news and human emotions, apart from just statistical data. To determine the impact that artificial intelligence can have on online journalism, an automatically generating information platform using AI has been developed. The objective is to generate a fully functional information platform that creates content and news articles automatically, which is achieved by analyzing internet trends, mining data related to the trends from other news sources, classifying the data, and categorizing and generating information to resemble those written by human journalists, both grammatically and linguistically. This is achieved with the help of machine learning and NLTK (Natural Language Toolkit) modules for Python which is used to process trends across social media platforms, especially Twitter.