Project Details
DARPA
The goal of DARPA’s Computational Simulation of Online Social Behavior (SocialSim) is to develop innovative technologies for high-fidelity computational simulation of online social behavior.
A simulation of the spread and evolution of online information, if accurate and at-scale, could enable a deeper and more quantitative understanding of use of the global information environment than is currently possible using existing approaches. High-fidelity (i.e., accurate, at-scale) computational simulation of the spread and evolution of online information would support efforts to analyze strategic disinformation campaigns, deliver critical information to local populations during disaster relief operations, and could potentially contribute to other critical missions in the online information domain.
The simulation of online information propagation at scale provides a method for developing a scientific understanding of several critical phenomena in sociology, psychology, economics, political science, and other human-related systems. The integration across disciplines and modeling approaches, and scales in some cases, has not yet matured into a set of standard methods nor has a set of example computational platforms become available for general use in government, academia, or industry.
To tackle this problem we have developed an agent-based modeling platform for the implementation of a set of methods that provide
- Development and testing of social, economic, and psychological theory at scale, and
- Providing predictive (in time) forecasting of information propagation, and
- Providing situational forecasting (what-if scenario simulation).
Key Findings
- Development of a paradigmatic view of social simulation based on a review of the state-of-the-art in modeling human systems
- Human social group behavior modeled as extended cognition makes sense
- Modeling agents with high-fidelity cognitive architectures is feasible at scale
- Development of a methodology for systematically integrating sociological, cognitive, and economic functions into a nested functional Bayesian agent.
- Development of a new semantic embedding method for social media platforms that is designed for interfacing with psychological models.
- Development of a semantic clustering method.
- Social psychological constructs implemented as simple computational agents can be used to predict future user belief production on social media.
- Sociological constructs implemented in agent-based representation of social media systems predicts the evolution of network structure.
Tools
Publications
Afrasiabi, M., Orr, M.G., and Austerweil, J.L.; “Evaluating Theories of Collaborative Cognition Using the Hawkes Process and a Large Naturalistic Data Set”; Paper presented at the Annual Meeting of the Cognitive Science Society; July 2019
Swarup, S.; “Adequacy: What Makes a Simulation Good Enough?”; Paper presented at the Spring Simulation Conference; May 2019
Orr, M.G.; “Multi-Scale Resolution of Human Social Systems: A Synergistic Paradigm for Simulating Minds and Society”; Social-Behavioral Modeling for Complex Systems; edited by Davis, P.K., O’Mahony, A., and Pfautz, J.; John Wiley & Sons, 2019, pp. 697-710.
Swarup, S., Marathe, A., Marathe, M.V., and Barrett, C.L.; “Simulation Analytics for Social and Behavioral Modeling”; Social-Behavioral Modeling for Complex Systems; edited by Davis, P.K., O’Mahony, A., and Pfautz, J.; John Wiley & Sons, 2019, pp. 617-632.
Orr, M.G., Lebiere, C., Stocco, A., Pirolli, P., Pires, B., and Kennedy, W.G.; “Multi-scale resolution of neural, cognitive and social systems”; Computational and Mathematical Organization Theory, 25 (2019): 4-23.
Orr, M.G., Lebiere, C., Stocco, A., Pirolli, P., Pires, B., and Kennedy, W.G.; “Multi-Scale Resolution of Cognitive Architectures: A Paradigm for Simulating Minds and Society”; Paper presented at the Association for the Advancement of Artificial Intelligence (AAAI) Fall Symposium; October 2018
Bhattacharya, P.; “The Matrix: An Agent-Based Modeling Framework for Complex Systems and Data Intensive Simulations”; Paper presented at the Dynamics On and Of Complex Networks Workshop (DOOCN-XI) at the Complex Systems Conference (Thessaloniki, Greece); September 2018
Orr, M.G., Lebiere, C., Stocco, A., Pirolli, P., Pires, B., and Kennedy, W.G.; “Multi-scale Resolution of Cognitive Architectures: A Paradigm for Simulating Minds and Society”; Social, Cultural, and Behavioral Modeling; edited by Thomson, R., Dancy, C., Hyder, A., and Bisgin, H.; Springer, 2018, pp. 3-15. [Presented at the International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction and Behavior Representation in Modeling and Simulation (SBP-BRiMS); July 2018]
Conference Presentations
Bhattacharya, P., Ekanayake, S., Kuhlman, C.J., Lebiere, C., Morrison, D., Swarup, S., Wilson, M.L., and Orr, M.G.; “The Matrix: An Agent-Based Modeling Framework for Data Intensive Simulations”; Talk presented at the International Conference on Autonomous Agents and Multiagent Systems (AAMAS); May 2019
Orr, M.G.; Panel presentation on Miscellaneous Topics; Invited panel presentation for “Physics of Information Processing” at the 3rd International Workshop on Social Sensing (Orlando, Florida); April 2018
Awards
Best Paper for the International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction and Behavior Representation in Modeling and Simulation (SBP-BRiMS) 2018