Proceedings of the 2021 Conference of The Computational Social Science Society of the Americas
Series: Springer Proceedings in Complexity;
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Product details:
- Edition number 1st ed. 2022
- Publisher Springer International Publishing
- Date of Publication 29 March 2022
- Number of Volumes 1 pieces, Book
- ISBN 9783030961879
- Binding Hardback
- No. of pages191 pages
- Size 235x155 mm
- Weight 477 g
- Language English
- Illustrations IX, 191 p. 78 illus., 68 illus. in color. Illustrations, black & white 249
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Long description:
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 2021 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.
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Table of Contents:
Chapter 1 - Effects of Assortativity on Consensus Formation with Heterogeneous Agents (Ece Mutlu and Ozlem Ozmen Garibay).- Chapter 2 - Quantifying Polish Anti-Semitism in Twitter: A Robust Unsupervised Approach with Signal Processing (Peter Chew).- Chapter 3 - On Modeling Evolution in Continuous Spaces (Robin Clark and Steven Kimbrough).- Chapter 4 - Economic Sanctions and Consumer Behavior in Target States: An Agent-Based Model of Boycott Movements (Rena Sung and Jonghyuk Park).- Chapter 5 - Scheduler dependencies in Agent-Based Models: A case-study using a contagion model (Srikanth Mudigonda; Santiago Nunez-Corrales; Rajesh Venkatachalapathy and Jeffrey Graham).- Chapter 6 - Exploring the Impact of Social Network Density and Agent Openness on Societal Polarization (Justin Mittereder; Robert Carroll; Brandon Frulla and Stephen Davies).- Chapter 7 - Learning Actor Preferences by Evolution (H Van Dyke Parunak).- Chapter 8 - Drivers and Predictors of COVID-19 Vaccine Hesitancy in Virginia (Asal Pilehvari; Jason Ton; Mukundan Ram Mohan; Achla Marathe and Anil Vullikanti).- Chapter 9 - The Spreading-Activation Framework Does Not Explain the Effects of Degree and Clustering on Spoken Word Recognition (Leo Niehorster-Cook).- Chapter 10 - Engineering Decentralized Enterprises: Emergent Mission Accomplishment without Centralized Command and Control (Michael Norman; Paul Silvey; Matthew Koehler and Kirbi Joe).- Chapter 11 - An Agent-Based Approach to Classical Competitive Prices (Jonathan Cogliano, Roberto Veneziani and Naoki Yoshihara).- Chapter 12 - Machine Learning Reveals Adaptive COVID-19 Narratives in Online Anti-Vaccination Network (Richard Sear; Rhys Leahy; Nicholas Johnson Restrepo; Yonatan Lupu and Neil Johnson).- Chapter 13 - Agentization of Two Population-Driven Models of Mathematical Biology(John Stevenson).
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