2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) (2018)
Aug. 28, 2018 to Aug. 31, 2018
Ajitesh Srivastava , Department of Computer Science, University of Southern California, Los Angeles
Robin Petering , Department of Social Work, University of Southern California, Los Angeles
Rajgopal Kannan , US Army Research Lab-West, Los Angeles
Eric Rice , Department of Social Work, University of Southern California, Los Angeles
Viktor K. Prasanna , Ming Hsieh Department of Electrical Engineering, University of Southern California, Los Angeles
Interventions to reduce violence among homeless youth are difficult to implement due to the complex nature of violence. However, a peer-based intervention approach would likely be a worthy approach as it has been shown that individuals who interact with more violent individuals are more likely to be violent, suggesting a contagious nature of violence. We propose Uncertain Voter Model to represent the complex process of diffusion of violence over a social network, that captures uncertainties in links and time over which the diffusion of violence takes place. Assuming this model, we define Violence Minimization problem where the task is to select a predefined number of individuals for intervention so that the expected number of violent individuals in the network is minimized over a given time-frame. We extend the problem to a probabilistic setting, where the success probability of converting an individual into non-violent is a function of the number of “units” of intervention performed on them. We provide algorithms for finding the optimal intervention strategies for both scenarios. We demonstrate that our algorithms perform significantly better than interventions based on popular centrality measures in terms of reducing violence.
A. Srivastava, R. Petering, R. Kannan, E. Rice and V. K. Prasanna, "How to Stop Violence Among Homeless: Extension of Voter Model and Intervention Strategies," 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), Barcelona, Spain, 2018, pp. 83-86.