{"product_id":"behavioral-computational-social-science-9781118657300","title":"Behavioral Computational Social Science","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eThis book is organized in two parts: the first part introduces the reader to all the concepts, tools and references that are required to start conducting research in behavioral computational social science.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003cp\u003ePreface ix\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 Introduction: Toward behavioral computational social science 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e1.1 Research strategies in CSS 2\u003c\/p\u003e \u003cp\u003e1.2 Why behavioral CSS 3\u003c\/p\u003e \u003cp\u003e1.3 Organization of the book 4\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart i CONCEPTS AND METHODS 7\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Explanation in computational social science 9\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e2.1 Concepts 10\u003c\/p\u003e \u003cp\u003e2.1.1 Causality 10\u003c\/p\u003e \u003cp\u003e2.1.2 Data 18\u003c\/p\u003e \u003cp\u003e2.2 Methods 19\u003c\/p\u003e \u003cp\u003e2.2.1 ABMs 19\u003c\/p\u003e \u003cp\u003e2.2.2 Statistical mechanics, system dynamics, and cellular automata 22\u003c\/p\u003e \u003cp\u003e2.3 Tools 25\u003c\/p\u003e \u003cp\u003e2.4 Critical issues: Uncertainty, model communication 27\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Observation and explanation in behavioral sciences 31\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e3.1 Concepts 32\u003c\/p\u003e \u003cp\u003e3.2 Observation methods 35\u003c\/p\u003e \u003cp\u003e3.2.1 Naturalistic observation and case studies 35\u003c\/p\u003e \u003cp\u003e3.2.2 Surveys 36\u003c\/p\u003e \u003cp\u003e3.2.3 Experiments and quasiexperiments 37\u003c\/p\u003e \u003cp\u003e3.3 Tools 38\u003c\/p\u003e \u003cp\u003e3.4 Critical issues: Induced responses, external validity, and replicability 40\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Reasons for integration 43\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e4.1 The perspective of agent]based modelers 44\u003c\/p\u003e \u003cp\u003e4.2 The perspective of behavioral social scientists 49\u003c\/p\u003e \u003cp\u003e4.3 The perspective of social sciences in general 54\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart iI BEHAVIORAL COMPUTATIONAL SOCIAL SCIENCE IN PRACTICE 57\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Behavioral agents 59\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e5.1 Measurement scales of data 61\u003c\/p\u003e \u003cp\u003e5.2 Model calibration 63\u003c\/p\u003e \u003cp\u003e5.2.1 Single decision variable and simple decision function 63\u003c\/p\u003e \u003cp\u003e5.2.2 Multiple decision variables and multilevel decision trees 65\u003c\/p\u003e \u003cp\u003e5.3 Model classification 67\u003c\/p\u003e \u003cp\u003e5.4 Critical issues: Validation, uncertainty modeling 70\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Sophisticated agents 73\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e6.1 Common features of sophisticated agents 75\u003c\/p\u003e \u003cp\u003e6.2 Cognitive processes 75\u003c\/p\u003e \u003cp\u003e6.2.1 Reinforcement learning 76\u003c\/p\u003e \u003cp\u003e6.2.2 Other models of bounded rationality 80\u003c\/p\u003e \u003cp\u003e6.2.3 Nature]inspired algorithms 80\u003c\/p\u003e \u003cp\u003e6.3 Cognitive structures 84\u003c\/p\u003e \u003cp\u003e6.3.1 Middle]level structures 85\u003c\/p\u003e \u003cp\u003e6.3.2 Rich cognitive models 86\u003c\/p\u003e \u003cp\u003e6.4 Critical issues: Calibration, validation, robustness, social interface 88\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Social networks and other interaction structures 91\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e7.1 Essential elements of SNA 93\u003c\/p\u003e \u003cp\u003e7.2 Models for the generation of social networks 99\u003c\/p\u003e \u003cp\u003e7.3 Other kinds of interaction structures 104\u003c\/p\u003e \u003cp\u003e7.4 Critical issues: Time and behavior 106\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 An example of application 109\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e8.1 The social dilemma 110\u003c\/p\u003e \u003cp\u003e8.1.1 The theory 111\u003c\/p\u003e \u003cp\u003e8.1.2 Evidence 113\u003c\/p\u003e \u003cp\u003e8.1.3 Our research agenda 114\u003c\/p\u003e \u003cp\u003e8.2 The original experiment 114\u003c\/p\u003e \u003cp\u003e8.3 Behavioral agents 116\u003c\/p\u003e \u003cp\u003e8.3.1 Fixed effects model 116\u003c\/p\u003e \u003cp\u003e8.3.2 Random coefficients model 117\u003c\/p\u003e \u003cp\u003e8.3.3 First differences model 118\u003c\/p\u003e \u003cp\u003e8.3.4 Ordered probit model with individual dummies 119\u003c\/p\u003e \u003cp\u003e8.3.5 Multilevel decision trees 121\u003c\/p\u003e \u003cp\u003e8.3.6 Classified heuristics 126\u003c\/p\u003e \u003cp\u003e8.4 Learning agents 127\u003c\/p\u003e \u003cp\u003e8.5 Interaction structures 127\u003c\/p\u003e \u003cp\u003e8.6 Results: Answers to a few research questions 128\u003c\/p\u003e \u003cp\u003e8.6.1 Are all models of agents capable of replicating the experiment? 129\u003c\/p\u003e \u003cp\u003e8.6.2 Was the experiment influenced by chance? 131\u003c\/p\u003e \u003cp\u003e8.6.3 Do economic incentives work? 133\u003c\/p\u003e \u003cp\u003e8.6.4 Why does increasing group size generate more cooperation? 135\u003c\/p\u003e \u003cp\u003e8.6.5 What happens with longer interaction? 136\u003c\/p\u003e \u003cp\u003e8.6.6 Does a realistic social network promote cooperation? 137\u003c\/p\u003e \u003cp\u003e8.7 Conclusions 138\u003c\/p\u003e \u003cp\u003eAppendix Technical guide to the example model 141\u003c\/p\u003e \u003cp\u003eA.1 The interface 142\u003c\/p\u003e \u003cp\u003eA.2 The code 145\u003c\/p\u003e \u003cp\u003eA.2.1 Variable declaration 146\u003c\/p\u003e \u003cp\u003eA.2.2 Simulation setup 152\u003c\/p\u003e \u003cp\u003eA.2.3 Running the simulation 157\u003c\/p\u003e \u003cp\u003eA.2.4 Decision-making 157\u003c\/p\u003e \u003cp\u003eA.2.5 Updating interaction structure and other variables 165\u003c\/p\u003e \u003cp\u003eReferences 173\u003c\/p\u003e \u003cp\u003eIndex 187\u003c\/p\u003e","brand":"John Wiley \u0026 Sons Inc","offers":[{"title":"Default Title","offer_id":49528834326871,"sku":"9781118657300","price":58.85,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781118657300.jpg?v=1731873203","url":"https:\/\/bookcurl.com\/products\/behavioral-computational-social-science-9781118657300","provider":"Book Curl","version":"1.0","type":"link"}