A System to Filter Unwanted Words Using Blacklists In Social Networks

Abstract — The best entertainment for the younger generation now is given in the form of Social Networking sites. The Online Social Networks (OSN) mainly helps an individual to connect with their friends, family and the society online in order to gather and share new experiences with others. Now-a-days, the OSNs are facing the problem of the people posting the indecent messages on any individual's wall which annoys other people on seeing them. In order to filter those unbearable messages a system called Machine Learning is introduced. The aim of the present work is therefore to propose and experimentally evaluate an automated system, called Filtered Wall (FW), able to filter unwanted messages from OSN user walls. We exploit Machine learning (ML) text categorization techniques to automatically assign with each short text messages a set of categories based on its content. The major efforts in building a robust short text classifier (STC) are concentrated in the extraction and selection of a set characterizing and discriminating features