Homo SocioNeticus: Scaling the Cognitive Foundations of Online Social Behavior
Abstract
The objective of Homo SocioNeticusa technological platform that was developed by a multi-site, multi-disciplinary team (Virginia Tech, Duke, Carnegie Mellon, IHMC, Stanford, U. Southern California, U. Wisconsin and Claremont Graduate U.) was to provide deep insight into the technical and theoretical best practices for and limitations of accurately scaling models of human cognition, perception, action and motivation to models of populations of cognitive agents that can accurately simulate online social behavioral phenomena (e.g., global information cascades, the evolution of information, and associated effects of social media platform). Central to our approach was the incorporation of substantive social behavioral theory (game theory, social cognition, social decision making, the sociology of human networks) into computational cognitive models of agents (to stand in as individual humans in our simulations). Our teamrepresented by world classexpertise in simulation and computational modeling of populations, cognitive simulation and modeling, computer science, social media analytics, sociology,economics, psychology, and decision theorydeveloped and operated a technical platform, called the Matrix, to run several large scale use cases of information.
Document Details
- Document Type
- Technical Report
- Publication Date
- Aug 26, 2020
- Accession Number
- AD1119549
Entities
People
- Christian Lebiere
- David Plaut
- Gleotidle Gonzales
- James D Moody
- Joseph L Austerweil
- Mark Orr
- Monica Capra
- Peter Pirolli
- Ron Fricker
- Stephen Reed
Organizations
- Carnegie Mellon University
- Claremont Graduate University
- Duke University
- Florida Institute for Human and Machine Cognition
- University of Southern California
- University of Wisconsin–Madison
- Virginia Tech