Shareen S. Anthony, Nitin A. Shelke
Abstract: Online Social Networks (OSNs) are today one of the most popular interactive medium to share, communicate, and distribute a significant amount of human life information. In OSNs, information filtering can also be used for a different, more responsive, function. This is owing to the fact that in OSNs there is the possibility of posting or commenting other posts on particular public/private regions, called in general walls. Information filtering can therefore be used to give users the ability to automatically control the messages written on their own walls, by filtering out unwanted messages. OSNs provide negligible amount of support prevent undesired messages on user walls. To propose and experimentally evaluate an automated system, called Filtered Wall (FW), able to filter unwanted messages from OSN user walls. The proposed work deals with the prepossessing steps which is used to decrease the size of the database containing the abusive words.
Keywords: Online Social Networks, Machine Learning, Filtering Rules, Content-based filtering, BLs