Identification of the source(s) of misinformation propagation utilizing identifying codes

Abstract

With billions of users, social networks have become the go to platform for information diffusion for news media outlets. Lately, certain entities (users and/or organizations) have been active in generating misinformation in order to attract users to their respective websites, to generate online advertisement revenues, to increase followers, to create political instability, etc. With the increasing presence of misinformation on social networks, it is becoming increasingly difficult to not only distinguish between information and misinformation, but also, to identify the source(s) of misinformation propagation. This effort reviews my doctoral research on identifying the source(s) of misinformation propagation. Particularly, I utilize the mathematical concept of Identifying Codes to uniquely identify users who become active in propagating misinformation. In this paper, I formally present the computation of the Minimum Identifying Code Set (MICS) as a novel variation of the traditional Graph Coloring problem. Furthermore, I present an Integer Linear Program for the computation of the MICS. I apply the technique on various anonymous Facebook network datasets and show the effectiveness of the approach.