A Comprehensive Analysis of News Classification Using NLP

Abstract

A growing number of people rely on online news providers for daily information and current events. As more individuals learn how helpful digital data can be, both its amount and frequency of use are expected to expand. With so many publications producing data, it may be hard for consumers to find what they need. Modern search engines offer so many results that only a small fraction are relevant to user requests. Adding a classifier to search engines may assist classify enormous amounts of data into specified categories. Inconsistencies have been found in the current news classification methods outlined in this survey article. To improve this, a good news categorization approach must use Natural Language Processing, feature extraction, Decision Making, and fuzzy list. The next paradigm research will define this method well.