FSAs: A Qualitative Analysis of Various Friend Suggestion Algorithms in Social Networks

Abstract

Social networks (SNWs) rely on effective friend suggestion algorithms (FSAs) that would enhance users’ connectivity and foster their engagement. This paper briefly compares some of the existing FSAs that are used for making such recommendations. By analyzing these algorithms, we identify their strengths and weaknesses and the way they leverage user data for making meaningful suggestions. Building on these insights, we further aim to propose a novel FSA that is based on individual user engagement and not on any form of triadic closure or past snapshot of the network.