Yang / von Briesen Proceedings of the 2020 Conference of The Computational Social Science Society of the Americas

1. Auflage 2021
ISBN: 978-3-030-83418-0
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 279 Seiten, eBook

Reihe: Springer Proceedings in Complexity

This book is comprised of the latest research into CSS methods, uses, and results, as presented at the 2020 annual conference of the Computational Social Science Society of the Americas (CSSSA). Computational social science (CSS) is the science that investigates social and behavioral dynamics through social simulation, social network analysis, and social media analysis. The CSSSA is a professional society that aims to advance the field of computational social science in all areas, including basic and applied orientations, by holding conferences and workshops, promoting standards of scientific excellence in research and teaching, and publishing research findings and results.

The above-mentioned conference was held virtually, October 8 – 11, 2020. What follows is a diverse representation of new results and approaches to using the tools of CSS and agent-based modeling (ABM) in exploring complex phenomena across many different domains.  Readers will therefore not only have the results of these specific projects upon which to build, along with a wealth of case-study examples that can serve as meaningful exemplars for new research projects and activities, they will also gain a greater appreciation for the broad scope of CSS.

Zielgruppe

Research

Autoren/Hrsg.

Yang, Zining

von Briesen, Elizabeth

Inhaltsverzeichnis

Dale Brearcliffe and Andrew Crooks: Creating Intelligent Agents: Combining Agent-Based Modeling with Machine Learning
Claudius Gros: Envy splits societies into a lower and a upper class
Marie Alaghband and Ivan Garibay: Effects of Non-Cognitive Factors on Post-Secondary Persistence of Deaf Students: An Agent-Based Modeling Approach
Andrew Collins: Comparing Agent-Based Modeling to Cooperative Game Theory and Human Behavior
Peter Chew and Jonathan Chew: Analyzing transnational narratives in Twitter: an unsupervised approach using PARAFAC
Santiago Núñez-Corrales, Milton Friesen, Srikanth Mudigonda, Rajesh Venkatachalapathy and Jeffrey Graham: In-Silico models with greater fidelity to social processes: towards ABM platforms with realistic concurrency
Saeed Langarudi, Carlos Silva and Sam Fernald: Dynamics of Information Perception in Management of CommonsH. Van Dyke Parunak: Psychology from Stigmergy
Ece Mutlu, Ivan Garibay and Amirarsalan Rajabi: CD-SEIZ: Cognition-Driven SEIZ Compartmental Model for the Prediction of Information Cascades on Twitter
Jiin Jung, Aaron Bramson, William Crano, Scott Page and John Miller: Cultural Drift, Indirect Minority Influence, Network Structure and Their Impacts on Cultural Change and Diversity
Leticia Izquiero, Gamaliel Palomo, Arnaud Grignard, Luis Alonso, Mario Siller and Kent Larson: An agent-based model to evaluate the perception of safety in informal settlements
William Leibzon: Study of Altruism as a Behavioral Trait in Game Theory Network Dynamics with Prisoner Dilemma Games
Matthew Koehler, David Slater, Garry Jacyna and James Thompson: Analyzing the potential impact of nonpharmaceutical interventions on the spread of COVID-19  (COVID-19 work in progress)
Shigeaki Ogibayashi: An Agent-Based Model of Infectious Diseases that Incorporates the Role of Immune Cells and Antibodies
Nicholas Willems, Cale Reeves, Vivek Shastry and Varun Rai: Heterogeneity in populations and behaviors: An agent-based model of the social spread of COVID-19  
Vivek Shastry, Cale Reeves, Nicholas Willems and Varun Rai: Work In Progress: COVID-19 Policy Evaluation (CoPE) Tool: An agent-based model for ex-ante evaluation of policy designs and behavioral responses to COVID-19
Amirarsalan Rajabi, Alexander Mantzaris, Ece Mutlu and Ivan Garibay: Investigating dynamics of COVID-19 spread and containment with agent-based modeling
Youngsun Hwang, Joseph Immormino and Glenn-Iain Steinback: Purchasing Power to the People: An Agent-Based Simulation of Pandemic Economic Recovery
Jacob Kelter, Andreas Bugler and Uri Wilensky: Agent-based models of Quadratic Voting
Brian Tivnan, Carl Burke, Matthew Koehler, Matthew Mcmahon And Jason Veneman: Towards a model of the national market system: fragmented and heterogenous venues
Hanin Alhaddad, Nisha Baral and Ivan Garibay: Online Rejection Influence on Behavior Deviancy and Radicalization: An Agent-Based Model Approach
Narjes Sadeghiamirshahidi, Anuj Mittal and Caroline Krejci: An agent-based model of digitally-mediated farmer transportation collaboration
Graham Sack: Geometries of Desire: Simulating Rene Girard’s Mimetic Theory
Mehdi Moghadam Manesh, Saeed Langarudi and Birgit Kopainsky: Can Institutionalization Prevent the Depletion of Groundwater Resources?

Über Autor(innen)

Dr. Zining Yang is Senior Manager at Southern California Edison. She also works as Clinical Professor at Claremont Graduate University and Associate Director at the TransResearch Consortium. She sits on the Board of the Computational Social Science Society of the Americas (CSSSA), and serves as Scientific Advisory Board Member for Human Factors and Simulations. Dr. Yang received her Ph.D. in Computational and Applied Mathematics and Political Economy from Claremont Graduate University in 2015. Her research interests include Data Analytics, Machine Learning, Modeling and Simulation, Complex Adaptive Systems, Agent-Based Models, and Network Analysis. Dr. Yang has been published numerous times in the fields of Computer Science, Economics, Public Policy, and Political Science. She has been identified as an outstanding researcher by the government, worked on a National Science Foundation-sponsored project, and won multiple awards from various organizations, including the Ministry of Education of the People’s Republic of China; International Social Computing, Behavioral Modeling and Prediction; and the International Institute of Informatics and Systemics.

 Dr. Elizabeth von Briesen is an Assistant Professor of Computer Science at Elon University, and is a member of the board of the Computational Social Science Society of the Americas. She received her Ph.D. in Computing & Informatics from the University of North Carolina at Charlotte in 2020. Her research interests are focused on the study of complex adaptive systems using computational techniques, particularly with respect to social systems experiencing identity-based conflict. She primarily works with agent-based models, and performs data mining and sentiment analysis to inform those simulations. Finally, in her current position, Dr. von Briesen strives to contribute toward an evolving undergraduate computer science experience through research, service, and high-quality, innovative teaching.