Modeling Social Contagion and Information Diffusion in Complex Socio-Technical Systems

Abstract

The rise of technology and social media has altered the human cognition, and we must rethink our approach toward information dissemination systems when dealing with topics such as social campaigns, advertising, false news outbreak, and more. In this article, we start by providing an overview of classical information spread dynamics using various macroscopic models, including the famous Maki–Thompson model. Building on these, we propose and design context-aware modeling frameworks capable of capturing specific scenarios in online social media information spread. We propose four context-aware macroscopic models capable of capturing the dynamics of information diffusion for a specific context. We also present stochastic versions of these models. Case studies using real Twitter data, along with an algorithm to construct ignorant–spreader–recovered (ISR) groups are presented to validate the proposed models.