ISBN:
9783319140117
Language:
English
Pages:
Online-Ressource (xii, 260 pages)
,
color illustrations
Edition:
Online-Ausg.
Series Statement:
Computational social sciences
Series Statement:
Computational Social Sciences Ser.
Parallel Title:
Print version Social Phenomena : From Data Analysis to Models
DDC:
300.1/5118
Keywords:
Social sciences Data processing
;
Social sciences Mathematical models
;
Mathematics
;
Electronic books
Abstract:
This book focuses on the new possibilities and approaches to social modeling currently being made possible by an unprecedented variety of datasets generated by our interactions with modern technologies. This area has witnessed a veritable explosion of activity over the last few years, yielding many interesting and useful results. Our aim is to provide an overview of the state of the art in this area of research, merging an extremely heterogeneous array of datasets and models. Social Phenomena: From Data Analysis℗ℓto Models is divided into two parts. Part I deals with modeling social behavior under normal conditions: How we live, travel, collaborate and interact with each other in our daily lives. Part II deals with societal behavior under exceptional conditions: Protests, armed insurgencies, terrorist attacks, and reactions to infectious diseases. This book offers an overview of one of the most fertile emerging fields bringing together practitioners from scientific communities as diverse as social sciences, physics and computer science. We hope to not only provide an unifying framework to understand and characterize social phenomena, but also to help foster the dialogue between researchers working on similar problems from different fields and perspectives
Description / Table of Contents:
Foreword; Preface; Contents; 1 Introduction; 1.1 Online Queries; 1.2 Twitter; 1.3 Cell Phones; 1.4 Bibliographic Databases; 1.5 Offline Interactions; 1.6 Structure of the Book; References; Part I Social Behavior Under Normal Conditions; 2 Modeling and Understanding Intrinsic Characteristicsof Human Mobility; 2.1 Introduction; 2.2 New Data Sources; 2.3 Individual Mobility Models; 2.4 Aggregate Mobility; 2.5 Human Behavior and Mobility; 2.5.1 Mobility and Disease Spread; 2.5.2 Mobility and Social Behavior; 2.5.3 Mobility and Economic Outcomes; 2.6 Conclusion; References
Description / Table of Contents:
3 Face-to-Face Interactions3.1 Introduction; 3.2 Proxies of Face-to-Face Interactions and Measurement Strategies; 3.3 Face-to-Face Interactions as Temporal Networks; 3.4 Structures and Structure Discovery; 3.4.1 Structures in Aggregated Data; 3.4.1.1 Contact Networks; 3.4.1.2 Contact Matrices; 3.4.1.3 Different Types of Contacts; 3.4.2 Longitudinal Structures; 3.4.2.1 Short-Term Stability; 3.4.2.2 Long-Term Stability; 3.4.3 Mesoscopic Structures and Latent Factor Analysis; 3.5 Modelling Face-to-Face Interactions; 3.6 Conclusions and Open Problems; References
Description / Table of Contents:
4 Modeling and Predicting HumanInfectious Diseases4.1 Introduction; 4.2 Basic Concepts in Mathematical Epidemiology; 4.2.1 Modeling Transitions Between Compartments; 4.2.2 The SIR Model; 4.2.2.1 Epidemic Threshold; 4.2.2.2 Disease-Free Equilibrium; 4.3 Beyond Homogeneous Mixing; 4.3.1 The SIR Model in Networks; 4.3.1.1 Epidemic Threshold; 4.4 Metapopulation Models; 4.5 Agent-Based Models; 4.6 Digital Epidemiology; 4.6.1 Social Media Based Epidemic Models; 4.7 Discussion; References; 5 Early Signs of Financial Market Moves Reflectedby Google Searches; 5.1 Introduction; 5.2 Results
Description / Table of Contents:
5.3 DiscussionAppendix; References; 6 Online Interactions; 6.1 Introduction; 6.1.1 Social Link Formation; 6.1.1.1 Classic Network Evolution Models; 6.1.1.2 Models with Social Components; 6.1.1.3 Link Prediction; 6.1.2 Communication Dynamics; 6.1.2.1 Threshold Model; 6.1.2.2 Homophily; 6.1.2.3 Weak Tie Hypothesis; 6.1.2.4 Limited Attention; 6.1.2.5 Communication Dynamics on Evolving Networks; 6.2 Case Study: Traffic-Based Social Link Formation; 6.2.1 Link Creation Mechanisms; 6.2.1.1 Statistical Analyses of Shortcuts; 6.2.1.2 User Preference; 6.2.1.3 Link Efficiency
Description / Table of Contents:
6.2.2 Rules of Network Evolution6.2.2.1 Simple Strategy; 6.2.2.2 Combined Strategies; 6.3 Discussion; References; 7 The Contagion of Prosocial Behavior and the Emergence of Voluntary-Contribution Communities; 7.1 Introduction; 7.1.1 The Puzzle of Online Generosity; 7.1.2 Outline of a Theory of Prosocial Contagion; 7.2 Testing Individual Mechanisms; 7.2.1 Online Experiment; 7.2.2 Results; 7.3 Extrapolating to Population Outcomes; 7.3.1 Simulation Model; 7.3.1.1 Assumptions; 7.3.1.2 Behavioral Rules; 7.3.1.3 Parameter Space; 7.3.2 Results; 7.4 Discussion; References
Description / Table of Contents:
8 Understanding the Scientific Enterprise: Citation Analysis, Data and Modeling
Note:
Includes index
URL:
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