Modeling and data analysis of the drivers of discontent, social cohesion, and resilient decision-making
Abstract
Modeling and data analysis of the drivers of discontent, social cohesion, and resilient decision-making PI: Maria R DÕOrsogna California State University at Northridge Cohesive societies are built on a shared sense of purpose and belonging, where individuals of different lived experiences are invested in common goals and unite in the face of challenges. Sustaining a cohesive society is an ongoing process that requires the willingness of citizens to engage and governmental policies to promote inclusivity, opportunity, and good management of collective resources. The absence of social cohesion may lead to discontent, erosion of trust, social unrest, degradation of shared resources, and even violence. The goal of this proposal is to develop new modeling and data analytic tools to i) understand drivers of mass mobilizations, ii) help promote social cohesion, and iii) foster resilient decision-making. i) Many databases exist to track social unrest in various parts of the world. However, few comprehensive efforts have been made to understand how the Òflow of discontentÓ propagates, and to correlate protests, rioting, and the eruption of violence with relevant geopolitical characteristics. We will use data science and network analysis to interface data from these social unrest trackers (theme and type of protest, geographical extent, duration) with several societal indicators and study the dynamics of protest propagation. Results will be used as a foundation to develop mathematical models of protest spread and escalation. We will adapt and expand existing representations of epidemiological trends and social contagion to the relatively less studied field of protest dynamics. ii) While many organizations and academic groups have focused on defining social cohesion and ranking communities through ad-hoc indices that subsume various components, few mathematical modeling efforts have been devoted to studying how social cohesion can be improved. Typical models of cooperation and trust are built on the concept of homophily, whereby individuals of similar traits tend to be more cooperative towards one another. The question we will ask is: what strategies can be developed to foster a sense of unity among people that may have different or even contrasting characteristics? We will develop game-theoretic models on a network to investigate the emergence of cooperative societies not based on Òin-groupÓ homophily, but where investments are made to promote Òcross-groupÓ activities (such as neighborhood or service projects) where repeated contact and exposure may lead to the emergence of trust and unity. iii) As humans we often tend to discount the consequences of our collective actions over the long term in favor of short-term gains, as in the case of resource conservation. How should governments determine their policies to most efficiently raise awareness and manage these resources? We will formulate this problem as a Markov Decision Process where the objective of the government is to preserve and/or improve quality and abundance of shared resources, while taking into account the effects of past mismanagement and resident behavior. The successful completion of this project will lead to the merging of real-world data from multiple sources using new models and methods in network science, decision-making processes, dynamical neural-network control, and stochastic phenomena. Our results will provide a better understanding of the conditions that lead to wide-spread unrest, the building of cohesive societies, and increased citizen engagement. We hope to offer tools that can help evaluate costs and benefits of local or regional intervention, optimize resource allocation, and stress test the consequences of given actions.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Apr 19, 2023
- Source ID
- W911NF2310129
Entities
People
- Maria-rita D Orsogna
Organizations
- Army Contracting Command
- California State University, Northridge
- United States Army