A ranking algorithm for online social network search

Abstract

Online Social Networks have become the new arena for people to stay in touch, pursue their interests and collaborate. In October 2012, Facebook reported a whopping 1 billion users which is testimony of the fact how online social networks have proliferated and made inroads into the real world. Some of the obvious advantages of social networks are (1) 24X7 availability allowing users to stay in virtual touch at any time of the day, (2) get in touch with people who have similar interests and collaborate with them and (3) the ability to be able to search for users to add to one's friend circle. The third advantage is the focus of this paper. With the increasing number of users on online social networks, it is important that when a user searches for another user, appropriate results are returned. This paper identifies three criteria - proximity, similarity and interaction, which can be used to rank search results so that more appropriate results are presented to the searching user. Also, this algorithm allows the search ranking to be customized according to the nature of the online social network in question. © 2013 ACM.