Majority Vote in Social Networks: Make Random Friends or Be Stubborn to Overpower Elites

09/29/2021
by   Charlotte Out, et al.
0

Consider a graph G, representing a social network. Assume that initially each node is colored either black or white, which corresponds to a positive or negative opinion regarding a consumer product or a technological innovation. In the majority model, in each round all nodes simultaneously update their color to the most frequent color among their connections. Experiments on the graph data from the real world social networks (SNs) suggest that if all nodes in an extremely small set of high-degree nodes, often referred to as the elites, agree on a color, that color becomes the dominant color at the end of the process. We propose two countermeasures that can be adopted by individual nodes relatively easily and guarantee that the elites will not have this disproportionate power to engineer the dominant output color. The first countermeasure essentially requires each node to make some new connections at random while the second one demands the nodes to be more reluctant towards changing their color (opinion). We verify their effectiveness and correctness both theoretically and experimentally. We also investigate the majority model and a variant of it when the initial coloring is random on the real world SNs and several random graph models. In particular, our results on the Erdős-Rényi and regular random graphs confirm or support several theoretical findings or conjectures by the prior work regarding the threshold behavior of the process. Finally, we provide theoretical and experimental evidence for the existence of a poly-logarithmic bound on the expected stabilization time of the majority model.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
12/05/2020

Majority Opinion Diffusion in Social Networks: An Adversarial Approach

We introduce and study a novel majority-based opinion diffusion model. C...
research
06/03/2020

Spread of Influence in Graphs

Consider a graph G and an initial configuration where each node is black...
research
05/28/2018

Opinion Forming in Binomial Random Graph and Expanders

Assume for a graph G=(V,E) and an initial configuration, where each node...
research
02/14/2023

Random Majority Opinion Diffusion: Stabilization Time, Absorbing States, and Influential Nodes

Consider a graph G with n nodes and m edges, which represents a social n...
research
02/24/2018

Importance of initial conditions in the polarization of complex networks

Most existing models of opinion formation use random initial conditions....
research
04/20/2020

A General Stabilization Bound for Influence Propagation in Graphs

We study the stabilization time of a wide class of processes on graphs, ...
research
07/18/2023

Minimum Target Sets in Non-Progressive Threshold Models: When Timing Matters

Let G be a graph, which represents a social network, and suppose each no...

Please sign up or login with your details

Forgot password? Click here to reset