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[null,"1.","Record Nr.",null,"UNISA996466846503316"]
[null,null,"Autore",null,"Yang Zining"]
[null,null,"Titolo",null,"Proceedings of the 2019 International Conference of The Computational Social Science Society of the Americas / / Zining Yang and Elizabeth von Briesen"]
[null,null,"Pubbl/distr/stampa",null,"Cham, Switzerland : , : Springer International Publishing, , [2021]"]
[{"$nulls":4},"©2021"]
[null,null,"ISBN",null,"3-030-77517-8"]
[null,null,"Descrizione fisica",null,"1 online resource (403 pages)"]
[null,null,"Collana",null,"Springer Proceedings in Complexity"]
[null,null,"Disciplina",null,"660.6"]
[null,null,"Soggetti",null,"Biotechnology"]
[{"$nulls":4},"Biotechnology - Safety measures"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"Intro -- Contents -- Editors and Contributors -- Social Impression of Faces: From Prediction to Modification -- 1 Introduction -- 2 Predicting Social Attributes of Faces -- 3 Creating a Large-Scale Facial Impression Dataset -- 4 Validating the Algorithm-Augmented Dataset -- 5 ModifAE: A Modification Model of Social Impressions -- 5.1 Architecture -- 5.2 ModifAE Training Procedure -- 5.3 How ModifAE Works -- 5.4 Qualitative Evaluation -- 5.5 Quantitative Evaluation -- 5.6 Qualitative Interpretations -- 6 Discussion -- References -- Corruption and the Effects of Influence Within Social Networks: An Agent-Based Model of the ``Lava Jato'' Scandal -- 1 Introduction -- 2 Background -- 3 The Model -- 3.1 Generation of Networks -- 3.2 Agents -- 3.3 Initialization of the Model and Agent Interactions -- 4 Results -- 5 Conclusion -- References -- Resistance of Communities Against Disinformation -- 1 Introduction -- 2 Opinion Dynamics -- 3 Model of Conspirators -- 4 Results -- 5 Discussion -- References -- Assessing the Potential of Crowd-Shipping for Food Rescue Logistics Using Agent-Based Modeling -- 1 Introduction -- 2 Models of Crowd-Shipping Systems -- 3 Agent-Based Model -- 3.1 Model Overview -- 3.2 Sub-Model 1: Restaurant Agent Decision-Making -- 3.3 Sub-Model 2: Shelter Assignment -- 3.4 Sub-Model 3: Crowd-Shipper Agent Decision-Making -- 3.5 Initialization -- 4 Experimentation and Results -- 5 Conclusion -- References -- Exogenous Shocks Lead to Increased Responsiveness and Shifts in Sentimental Resilience in Online "]
[{"$nulls":4},"Discussions -- 1 Introduction -- 2 Background -- 3 Methodology -- 3.1 Data -- 3.2 Conversation Dynamics -- 3.3 Sentiment Transfer -- 3.4 Transfer Entropy -- 4 Results -- 4.1 Conversation Dynamics -- 4.2 Sentiment Transfer -- 4.3 Total Transfer Entropy -- 5 Conclusion -- References -- The Cat and Mouse of Getting Around the Law."]
[{"$nulls":4},"1 Introduction -- 2 Results -- 3 Optimizing Strategies -- 3.1 Fast and Strong (\"All in\") -- 3.2 Slow and Strong (\"Slow and Aggressive\") -- 3.3 Fast and Weak -- 3.4 Slow and Weak (\"Do Nothing\") -- 4 Discussion -- 5 Conclusion -- References -- The Degree-Dependent Threshold Model: Towards a Better Understanding of Opinion Dynamics on Online Social Networks -- 1 Introduction -- 2 Methods -- 2.1 Data Set and Twitter Analysis Results -- 2.2 Generating Networks -- 2.3 Assigning Thresholds -- 2.4 Running Simulations -- 3 Simulation Results -- 4 Conclusion -- References -- Modeling Genocide: An Agent-Based Model of Bystander Motivations and Societal Restraints -- 1 Introduction -- 1.1 Review of Prior Work -- 1.2 Addressing the Research Gap -- 2 Research Approach -- 2.1 Social Science Theories -- 2.2 ABM Implementation -- 3 Results -- 3.1 Experiment 1: Effect of Contagion and Fear on Violence -- 3.2 Experiment 2: Sensitivity Analysis-System-Level Factors of Restraint () -- 4 Conclusions and Future Work -- References -- Global News Sentiment Analysis -- 1 Introduction -- 2 Related Work -- 3 Methodology and Experimentation -- 4 Results -- 4.1 Initial Observation -- 4.2 Comparison of Four Sentiment Analysis Tools -- 4.3 Three Article Processing Approaches -- 5 Discussion -- 6 Conclusion -- References -- An Agent-Based Model of Social Fabric Seen as an Emergent Behavior -- 1 Introduction -- 2 Social Fabric -- 3 Modeling Social Fabric in Cities -- 3.1 Conceptual Model -- 3.2 Agent-Based Model -- 4 Case Study: The Miramar Region -- 4.1 Mobility Patterns and Its Relationship with Perception -- 4.2 Encounters -- 5 Conclusion -- References -- Deep Agent: Studying the Dynamics  of Information Spread and Evolution  in Social Networks -- 1 Introduction -- 2 Challenge Problem Description -- 3 Methodology -- 3.1 Deep Agent Framework: Architecture and Analysis."]
[{"$nulls":4},"3.2 Agent-Based Models -- 4 Dataset Description -- 4.1 Evaluation Events and Metrics -- 5 Experimental Results -- 6 Conclusion and Future Work -- References -- Electoral College: Emergent Battlegrounds An Agent-Based Model of Campaign Behavior Change with District Allocation of Electors -- 1 Introduction -- 2 Background -- 3 Methodology -- 4 The Model -- 5 Validation -- 6 Results -- 7 Discussion and Conclusions -- References -- Social Viscosity, Fluidity, and Turbulence in Collective Perceptions of Color: An Agent-Based Model of Color Scale Convergence -- 1 Introduction: Social Viscosity, Fluids, and Turbulence -- 2 Social Meaning and the Analysis of Proximity -- 2.1 Meaning and Viscosity in Color Agents -- 3 An Agent-Based Model of Color Proximity -- 4 Case Study: Nucleation in Circular Color Scales -- 4.1 Methods -- 4.2 All-to-all Interactions -- 4.3 N Nearest-Neighbor Interactions -- 5 Discussion -- 6 Conclusions and Further Work -- References -- Inside the Mind of the Nonfiler: An Agent-Based Modeling Approach -- 1 Introduction -- 1.1 Brief Overview of Nonfilers and IRS Enforcement/Outreach -- 1.2 Current IRS Nonfiler Research -- 1.3 Past Uses of Agent-Based Models (ABMs) at RAAS -- 2 Methods -- 2.1 Agent-Based Model Overview -- 2.2 Econometric Modeling -- 3 Data -- 4 Results -- 4.1 Agent-Based Model -- 5 Discussion -- 5.1 Agent-Based Model -- 6 Conclusions and Future Work -- 6.1 Future Work -- Appendix-Overview, Design Concepts and Details, and Decision Making (ODD + D) Protocol Documentation of the Nonfiler Decision Model -- Purpose -- Entities, "]
[{"$nulls":4},"State Variables, Scales -- Process Overview and Scheduling -- Design Concepts -- Initialization -- Input Data -- Submodels -- References -- Capturing the Effects of Gentrification on Property Values: An Agent-Based Modeling Approach -- 1 Introduction -- 2 Related Work -- 3 Model Design -- 3.1 Data."]
[{"$nulls":4},"3.2 Environment -- 3.3 Agent Classes -- 3.4 Gentrification Calculation -- 3.5 Verification -- 4 Results -- 4.1 Gentrification by Supply -- 4.2 Gentrification by Demand -- 5 Discussion and Further Works -- 5.1 Main Results -- 6 Conclusion -- References -- Negative Influence Gradients Lead to Lowered Information Processing Capacity on Social Networks -- 1 Introduction -- 2 Related Work -- 3 Method -- 4 Results -- 5 Discussion -- 6 Conclusion -- References -- A Complex-Systems Agenda for Influencing Policy Studies -- 1 Introduction -- 1.1 Purpose -- 1.2 Our Definitions -- 1.3 Additional Discussion of Definitions -- 2 Worldview -- 2.1 System Thinking -- 2.2 Confronting Complexity and Wicked Problems -- 2.3 Decision-Making as a Continuing and Messy Process -- 2.4 The Values and Objectives that Drive Decisions -- 2.5 Knowledge, Uncertainty, and Disagreement -- 2.6 Moderation in the Search for Control -- 3 Basis for Reasoning and Inference -- 3.1 Theory, Data, Association, and Causation -- 3.2 Types of Theory -- 4 Analytic Style -- 4.1 Analysis and Reductionism, Both Good and Bad -- 4.2 Character of Analysis: Quantitative Versus Qualitative, and Matters of Rigor -- 4.3 Confronting Uncertainty and Disagreement -- 4.4 Comparing Options -- 4.5 Changing the Questions Asked of Simulation -- 5 Character of Models and Model-Based Analysis -- 5.1 Different Classes of Model -- 5.2 Purpose of Models and Related Issues of Validity -- 5.3 Measures of Outcome -- 5.4 Predict and Act Versus Anticipate Possibilities and Act Adaptively -- 6 Conclusions -- 6.1 Implications for Teaching Policy Studies -- 6.2 Implications for Computational Social Science -- References -- Wealth Dynamics in the Presence of Network Structure and Primitive Cooperation -- 1 Introduction -- 2 Model -- 2.1 Mathematical Formulation -- 2.2 Implementation -- 3 Verification."]
[{"$nulls":4},"3.1 Agent and Proto Life History -- 3.2 Gini Coefficient History -- 4 Analysis -- 4.1 Gini Coefficient -- 4.2 Life Expectancy -- 4.3 Interpretations, Conjectures, and Next Steps -- 5 Conclusion and Future Work -- References -- Social Primitives: Exploring Spark of Life Collective Behavior in Agent-Based Models -- 1 Introduction -- 2 Examples of Agent-Based Social Primitives -- 2.1 Ring World -- 2.2 Conway-Game of Life -- 2.3 Complexity Adaptive Systems-Page and Miller -- 2.4 Hammond-Tobacco and Policy-Low-Dimensional and High-Dimensional Models -- 3 Taxonomy of Social Primitives -- 3.1 Agent Description -- 3.2 Coding Agents and the Challenge of Implicit Assumptions -- 3.3 Environment Description -- 3.4 Coding the Environment and the Challenge of Implicit Assumptions -- 4 Coding a Social Primitives Model: The SPECscape Model -- 4.1 Agent to Agent Interaction -- 4.2 Agent-Environment Interaction -- 4.3 Anthropomorphic Crossover -- 5 Running the SPECscape Model -- 5.1 SPECscape Model and Gini Index -- 5.2 Four Landscape Starting Points -- 5.3 The Effect of Exogenous Shocks at Various Stages of Model Evolution -- 5.4 Models with and without Proto-institutions -- 6 Conclusion -- 6.1 Elements of Collective Function -- 6.2 Determining Anthropomorphic Leaps -- 6.3 Determining a Parameter-Based Measure of Model Complexity -- 6.4 Possibilities for Increasing the Complexity of SPECscape Model -- Appendix -- References -- Capturing the Production of Innovative Ideas: An Online Social Network Experiment and ``Idea Geography'' Visualization -- 1 Introduction -- 2 Online Social Network Experiment -- 2.1 Experimental Procedure -- "]
[{"$nulls":4},"2.2 Collective Design Tasks -- 3 Data Analysis Methods -- 3.1 Doc2Vec -- 3.2 Principal Component Analysis -- 3.3 Idea Geography -- 4 Results -- 4.1 Experiment Session I: Catch Phrase Design -- 4.2 Experiment Session II: Story Design."]
[{"$nulls":4},"5 Discussions."]