A Framework for Knowledge Discovery from Facebook

Abstract

In the 21st century Social Network became one of the most popular and easiest platforms for sharing information. Millions of people daily share billions of information over social networking site. Facebook is the most popular social media network around the globe today. It has a global audience of 1,230 million users. With the increasing number of posts, possibility of fake / illegal post are also being increase. Careless use of social media by user can also have a negative effect on their digital reputation. Effective analysis plays an important role in the social media crime investigation. Whenever an activity is conducted on social networks various controlling attributes are generated. So by analysing controlling attributes it is possible to investigate public activities and filter out the disruptive activities. In this paper structural information of Facebook, Facebook Query Language (FQL) and activity analysis using FQL are explored. A frame works for classify the end user by examine the flow of attributes for an activities is also presented. 

Keywords: Social Network, Facebook, Graph Explorer, Activity, Facebook Query Language, Classification