Carmichael / Yang Proceedings of the 2018 Conference of the Computational Social Science Society of the Americas

1. Auflage 2020
ISBN: 978-3-030-35902-7
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 291 Seiten, eBook

Reihe: Springer Proceedings in Complexity

This book contains a selection of the latest research in the field of Computational Social Science (CSS) methods, uses, and results, as presented at the 2018 annual conference of the CSSSA. This conference was held in Santa Fe, New Mexico, October 25 – 28, 2018, at the Drury Plaza Hotel.CSS investigates social and behavioral dynamics in both nature and society, through computer simulation, network analysis, and the science of complex systems. The Computational Social Science Society of the Americas (CSSSA) is a professional society that aims to advance the field of CSS in all its areas, from fundamental principles to real-world applications, by holding conferences and workshops, promoting standards of scientific excellence in research and teaching, and publishing novel research findings.  What follows is a diverse representation of new approaches and research findings, using the tools of CSS and Agent-Based Modeling (ABM) in exploring complex phenomena across manydifferent domains. Readers will not only have the methods and results of these specific projects on which to build, but will also gain a greater appreciation for the broad scope of CSS, and have a wealth of case-study examples that can serve as meaningful exemplars for new research projects and activities. This book, we hope, will appeal to any researchers and students working in the social sciences, broadly defined, who aim to better understand and apply the concepts of Complex Adaptive Systems to their work.

Zielgruppe

Research

Autoren/Hrsg.

Carmichael, Ted

Yang, Zining

Inhaltsverzeichnis

Chapter1. Exposing bot activity with PARAFAC tensor decompositions.- Chapter2. To Share or Not to Share: Effect of Peer-to-Peer Mentoring on Dynamics of Graduate Life.- Chapter3. How to code algorithms to favor public goods over private ones.- Chapter4. Institutional Emergence and the Persistence of Inequality in Hamilton, ON 1851-1861.- Chapter5. Identifying the Risk of Clinical Trial Failures: A Text Mining Approach.- Chapter6. Islamic Extremism and the Crystallization of Norms: An Agent-Based Model of Prison Radicalization.- Chapter7. An Agent-based Modeling for Simulating Land Degradation and Food Shortage in North Korea.- Chapter8. Alleviating Traffic Congestion by the Strategy of Modal Shift from Private Cars to Public Transports: A Case of Dhaka City, Bangladesh.- Chapter9. What Can Honeybees Tell Us about Social Learning?.- Chapter10. Understanding the Impact of Farmer Autonomy on Transportation Collaboration using Agent-based Modeling.- Chapter11. The Transmission of Information in Random Social Networks.- Chapter12. Does Socioeconomic Feedback Matter for Water Demand Models?.- Chapter13. A Popularity-Based Model of the Diffusion of Innovation on GitHub.- Chapter14. Segregation-sensitivity and Threshold-dependency in Residential Segregation.- Chapter15. Revisiting Markov Models of Intragenerational Social Mobility.- Chapter16. NetLogo meets Discrete Event Simulation.- Chapter17. Priming the W-O-M pump: Seeding Information to Increase Solar PV Adoption.- Chapter18. Modeling Schools’ Capacity for Lasting Change: A System Dynamics and Simulation-Based Approach.- Chapter19. Model Structure of Agent-Based Artificial System for Reproducing Bullying Phenomenon.- Chapter20. Predictors of Rooftop Solar Adoption in Rural Virginia.- Chapter21. Using Agent-Based Modeling to Analyze Systemic Risk Within the Housing Market.- Chapter22. The Impact of Indirect Minority Influence on Diversity of Opinion and the Magnitude, Speed and Frequency of Social Change.- Chapter23. Understanding Power-Law Behaviors in Surname Distribution: An Agent-Based Analysis.- Chapter24. Evaluation Of Simulated Agent – Based Computational Models Of Civil Violence With the Boko Haram Conflict.- Chapter25. The Marginal Effects of Immigration Enforcement.

Über Autor(innen)

Dr. Ted Carmichael is the Senior Research Scientist for TutorGen, a Carnegie Mellon start-up in the Education Technology space; and an Affiliated Assistant Research Professor in the Department of Software and Information Systems at the University of North Carolina, Charlotte (UNC Charlotte). Dr. Carmichael is currently serving as Vice President of the Computational Social Science Society of the Americas (CSSSA). He received his PhD in Computer Science,along with a certificate in Cognitive Science, in 2010 from UNC Charlotte. His primary research interests include modeling and simulation of complex systems, Educational Data Mining, and Intelligent Tutoring Systems; and he has published in a wide variety of fields, such as Computer Science, Economics, Biology, Sociology, Ecology, and Political Science. Dr. Carmichael has successfully served as PI or Co-PI on multiple grants, including for the National Science Foundation, the US Department of Education, and theKentucky Science and Engineering Foundation. His dissertation won the Distinguished Dissertation Award for 2010 at UNC Charlotte. Dr. Zining Yang is Data Science Advisor at Southern California Edison. She also works as Clinical Professor at Claremont Graduate University and Associate Director at 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 PhD 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 numerous publications in the fields of Computer Science, Economics, Public Policy, and Political Science. She has been identified as 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 People’s Republic of China; International Social Computing, Behavioral Modeling and Prediction; and International Institute of Informatics and Systemics.