Ego Network Analysis Using Machine Learning Algorithms

Abstract

The rise in social networking sites has led to overwhelming and chaotic amount of personal network traffic necessitating the need for optimizing techniques in management social media Websites like Google+, Facebook, and Instagram which gives individuals the opportunity to create social circles virtually, but this model demands abundant amount of time, and it is hard, maintaining the connections of individual users0 which increase. The problem is clustering problems on the users ego network or the network of friendships among friends. The radical increase of data on the Web as promoted a desire to extract only usable information from it, including information, sharing evaluation, and relationships within groups. This review paper is a summary of prior work in related fields and examines the drawbacks of community discovery in social media platforms. The motive of this research paper is to pinpoint each user’s circles within their social network, separating from other users who are not in their virtual social circle. This research paper is motivated by the need to identify and apply only the usable information from the Web and to optimize the management of personal social networks.