Impact of reciprocity in information spreading using epidemic model variants

Abstract

The use of online social networks has become a standard medium of social interactions and information spreading. Due to the significant amount of data available online, social network analysis has become apropos to the researchers of diverse domains to study and analyse innovative patterns, friendships, and relationships. Message dissemination through these networks is a complex and dynamic process. Moreover, the presence of reciprocal links intensify the whole process of propagation and expand the chances of reaching to the target node. We therefore empirically investigated the relative importance of reciprocal relationships in the directed social networks affecting information spreading. Since the dynamics of the information diffusion has considerable qualitative similarities with the spread of infections, we analysed six different variants of the Susceptible-Infected (SI) epidemic spreading model to evaluate the effect of reciprocity. By analysing three different directed networks on different network metrics using these variants, we establish the dominance of reciprocal links as compared to the non-reciprocal links. This study also contributes towards a closer examination of the subtleties responsible for maintaining the network connectivity.