Weak dynamic monopolies in social graphs

TL;DR

This paper introduces the concept of weak dynamic monopolies to model influence spread in social networks where influence can be temporary, providing bounds, relationships, and complexity results for their size and processing time.

Contribution

It defines weak dynamic monopolies, explores their properties, bounds their size, analyzes processing time, and proves inapproximability results for their minimal size.

Findings

Bounds on the size of weak dynamic monopolies

Relationships with other influence models

Hardness of approximating minimal size

Abstract

Dynamic monopolies were already defined and studied for the formulation of the phenomena of the spread of influence in social networks such as disease, opinion, adaptation of new product and etc. The elements of the network which have been influenced (e.g. infected or adapted an opinion) are called active vertices. It is assumed in these models that when an element is activated, it remains active until the end of the process. But in some phenomena of the spread of influence this property does not hold. For example in some diseases the infection lasts only a limited period of time or consider the spread of disease or propagation of computer virus together with some quarantination or decontamination methods. Dynamic monopolies are not useful for the study of these latter phenomena. For this purpose, we introduce a new model for such diffusions of influence and call it weak dynamic monopoly. A social network is represented by a graph $G$. Assume that any vertex $v$ of $G$ has a threshold $\tau(v)\in \Bbb{N}$. Then a subset $D\subseteq V(G)$ is said to be a weak dynamic monopoly if $V(G)$ can be partitioned into $D_0=D, D_1, \ldots, D_k$ such that for any $i$, any vertex $v$ of $D_i$ has at least $\tau(v)$ neighbors in $D_{i-1}$. In this definition, by the size and the processing time of $D$ we mean $|D|$ and $k$, respectively. We first investigate the relationships between weak dynamic monopolies and other related concepts and then obtain some bounds for the smallest size of weak dynamic monopolies. Next we obtain some results concerning the processing time of weak dynamic monopolies in terms of some graph parameters. Finally, a hardness result concerning inapproximibility of the determining the smallest size of weak dynamic monopolies in general graphs is obtained.