CLASSIFICATION OF UNWANTED MESSAGES IN ONLINE SOCIAL NETWORK USING MACHINE LEARNING ALGORITHMS

Abstract

This One major fact in today's technical world, people are very active users of Online Social Networks. They share every details of their day to day life and are in touch with their loved ones no matter in which part of the world they live. The main issue is the ability to control the messages that are posted in the user's private message or walls to detect and negotiate unwanted messages. This work focus on predicting the emotions of a particular message or post in various OSN like twitter, blogs etc for emotion analysis so as to filter the messages which are inappropriate. This paper focuses on collecting corpus for sentimental analysis and performs linguistic analysis and machine learning techniques for predicting emotions accurately. Using the corpus we define distinct emotions and filter unwanted messages.