Author : Geethika K 1
Date of Publication :7th November 2016
Abstract: Online Social Networking (OSN) sites are always helpfulforbeingsocializedand togetexposedtoasocial environment. But, privacy and prevention of undesired posts on user wallis the only problem of biggest concern. User should have the ability to control the message posted on their own private wall to avoid undesirable contents to be displayed. The existing OSN sites have very little support regarding this problem. For example, Facebook filters messages on the basis of identity of senderi.e. only friend, friend of friend or group of friends can post any message; no content based preferences are supported. Taking this fact into consideration, the proposed work contributes to address such problem through a machine learning baseds of the classifie for labeling messages in support of contents of message. This work experimentally evaluates an automated scheme to filter out unwanted messages posted on Facebook walls by as signing a set of categories with each short text message based on its contents.
Reference :