Intervention Strategies and the Diffusion of Collective Behavior

Authored by Hai-hua Hu, Wen-tian Cui, Jun Lin

Date Published: 2015

Sponsors: Chinese National Natural Science Foundation

Platforms: MATLAB

Model Documentation: Other Narrative Pseudocode Mathematical description

Model Code URLs: https://www.comses.net/codebases/4212/releases/1.0.0/

Abstract

This paper examines the intervention strategies for the diffusion of collective behavior, such as promoting innovation adoption and repressing a strike. An intervention strategy refers to controlling the behaviors of a small number of individuals in terms of their social or personal attributes, including connectivity (i.e., the number of social ties one holds), motivation (i.e., an individual's intrinsic cost-benefit judgment on behavior change), and sensitivity (i.e., the degree to which one follows others). Extensive agent-based simulations demonstrate that the optimal strategy fundamentally depends on the goal and time of intervention. Moreover, the nature of the social network (determined by homophily type and level) moderates the effectiveness of a strategy. These results have substantial implications for the design and evaluation of intervention programs.

Tags

Social networks models Dynamics Adoption Heterogeneity Innovation Diffusion opinion leaders Density Spread Public-opinion