The Oxford Handbook of Social Networks (OXFORD HANDBOOKS SERIES)

"Social networks fundamentally shape our lives. Networks channel the ways that information, emotions, and diseases flow through populations. Networks reflect differences in power and status in settings ranging from small peer groups to international relations across the globe. Network tools even provide insights into the ways that concepts, ideas and other socially generated contents shape culture and meaning. As such, the rich and diverse field of social network analysis has emerged as a central tool across the social sciences. This Handbook provides an overview of the theory, methods, and substantive contributions of this field. The thirty-three chapters move through the basics of social network analysis aimed at those seeking an introduction to advanced and novel approaches to modeling social networks statistically. The Handbook includes chapters on data collection and visualization, theoretical innovations, links between networks and computational social science, and how social network analysis has contributed substantively across numerous fields. As networks are everywhere in social life, the field is inherently interdisciplinary and this Handbook includes contributions from leading scholars in sociology, archaeology, economics, statistics, and information science among others"-- Provided by publisher Cover The Oxford Handbook of Social Networks Copyright Table of Contents Acknowledgments Editor Biographies Contributor Biographies Chapter 1: Introduction The Handbook as a Map Network Basics and Theories Network Methods Network Dimensions Network Landscape Conclusions, Concerns, and Future Directions Note References Part I: Network Basics and Theory Chapter 2: Network Basics: Points, Lines, and Positions The Building Blocks of Networks Two General Approaches to Social Network Analysis Basic Network Forms Network Building Blocks: Bridging Levels Boundary Specification Connectivity, Cohesion, and Community Statistical Models of Networks Collecting Social Network Data Name Generators Network Sampling Ethics and Social Network Analysis Conclusion Note References Chapter 3: Theories of Social Networks Networks and Theory Action Theory and Social Capital Social Structures and Individual Action Social Capital Pragmatism and Interactionism Relational Sociology Social Networks and Meaning Extensions Conclusion Notes References Chapter 4: Networks and Neo-Structural Sociology Individual and Collective Capacities Interdependencies in the Organizational Society: Bureaucracy and Collegiality Relational Infrastructures Social Processes as Social Capital of the Collective in the Organizational and Market Society Neo-Structural Institutionalism Challenges: Longitudinal and Multilevel Network Structures to Navigate Social Processes Conclusion References Chapter 5: Rethinking Social Networks in the Era of Computational Social Science Four Conceptualizations of Network Ties for Social Network Theory Social Ties as Access or Opportunity Social Ties as (Time-Aggregated) Behavioral Interactions Social Ties as Interpersonal Sentiments Social Ties as Socially Constructed Role Relations Comparing These Four Conceptualizations Treatment of Ties and Null Ties Temporality Dilemmas of Mapping Theories to Data across Discrepant Conceptualizations of Networks Can We Use Role Relation Data to Investigate Theories of Social Interaction, Access, and Sentiments? Can We Use Aggregated Social Interaction Data to Investigate Theories of Access and Social Sentiments? A Revolution in Data Collection: Computational Social Science Computational Social Science and Role Relations Computational Social Science and Sentiments Computational Social Science and Behavioral Interactions Computational Social Science and Structures of Access or Opportunity A Revolution in Data Analysis: From Aggregating to Modeling Relational Events Acknowledgments Notes References Chapter 6: Networks, Status, and Inequality Terminology and Scope Networks Status Inequality Ascertaining Status in Networks Esteem and Choice Visibility and Prominence Agonism Status Production and Maintenance in Networks The Popularity Tournament The Facebook Effect Status Diffusion Asymmetry and Evolution Topological Implications of Status Studying Networks in Unequal Environments Conclusion Notes References Part II: Networks Methods Chapter 7: Strategies for Collecting Social Network Data: Overview, Assessment, and Ethics What Is the Goal? Theory’s Role in Gathering Network Data Design Strategies for Sampling and Measurement The “Boundary Specification” Problem Name Generators—Which Relationships? Name Interpreters—Information about Identified Social Ties Data Quality and Assessment: Did We Capture What We Intended to Capture? Tie Reliability and Validity Implications and Quality Assessment Strategies for Optimizing Data Fidelity Cognitive Social Structures Unique Ethical Considerationsof Network Data Ethics in Data Collection Ethics in Data Analysis and Presentation of Results Summary Notes References Chapter 8: Social Network Experiments What Is an Experiment? Can Social Networks Be Studied with Experiments? Experimental Manipulations for the Study of Social Networks Examples of Network Experiments Homophily and the Spread of Health Behaviors Networks and the Matthew Effect Error and Error Correction Process in Network Diffusion Network Recall and Social Exclusion Conclusion Notes References Chapter 9: The Network Scale-Up Method Introduction Methodology The Network Scale-Up Estimator Estimating Degree Bayesian Approach Generalized Network Scale-Up Survey Design Defining “Know” The Scaled-Down Condition Conclusion References Chapter 10: The Continued Relevance of Ego Network Data Advantages and Disadvantages of Ego Network Data Advantages Disadvantages What Can Be Extracted from Ego Network Data? Applications of Ego Network Data Using Ego Network Properties to Predict Individual-Level Outcomes Using Ego Network Data to Measure Social Boundaries Using Ego Network Data to Improve RDS Estimation Using Ego Network Data to Infer Full Network Features Conclusion: Future Uses of Ego Network Data Notes References Chapter 11: Dyadic, Nodal, and Group-Level Approaches to Study the Antecedents and Consequences of Networks: Which Social Network Models to Use and When? A Framework of Basic Models for Social Network Analysis at Different Levels Network Antecedents at a Dyadic Level (Model 1.1) Network Consequences at a Dyadic Level (Model 1.2) Network Emergence at the Nodal Level (Model 1.3) Network Consequences at the Nodal Level (Model 1.4) Network Emergence at a Group Level (Model 1.5) Network Consequences at a Group Level (Model 1.6) Variations and Extensions of the Six Basic Models Network Mediation Models Network Moderation Models Network Coevolution Model Multiple Groups and Multilevel Models for Dyadic and Nodal-Level Analysis Generalizability Group-Level Effects Cross-Level Interaction Macro-Micro-Macro Models Conclusion Acknowledgments Notes References Chapter 12: An Introduction to Statistical Models for Networks Some History Some More Notation Exponential Family of Random Graphs—p* Statistical Theory Parameters Simulation, Estimation, and Goodness of Fit Other Types of Networks Bipartite Networks Multilevel Networks Multivariate Networks Longitudinal Models Longitudinal Networks: Evolution of Structure or Coevolution of Structure and Attributes Conclusion Acknowledgements Notes References Chapter 13: Advances in Exponential Random Graph Models ERGM and ALAAM Model Constructs Multilevel ERGMs and ALAAMs Modeling Techniques Empirical Examples Empirical Example 1: Multiple Project Memberships and Advice Seeking in Organizations Example 2: Common Resource Management Satisfaction and Information Exchanges between Users Example 3: How Are Individual Accomplishments Shared across the Team? Discussion and Future Steps Notes References Chapter 14: Modeling Network Dynamics Conceptualizing Network Dynamics Network Change Processes Nodal Effects Dyadic Effects Endogenous Structure Modeling Network Dynamics The Relational Event Framework Stochastic Actor-Oriented Framework The Exponential Random Graph Framework Model Selection Empirical Example of Three Approaches Model Statistics Attribute Effects: Age Dyadic Effects: Proximity Endogenous Effects: Reciprocity Endogenous Effects: Triadic Closure Modeling Strategy and Results Baseline Models More Practical Models Extended Models Subsequent Steps Outstanding Issues and Future Directions Notes References Chapter 15: Causal Inference for Social Network Analysis The Influence Process Randomized Experiments Observational Studies Simulation Example of Identification Using OLS Informing the Inevitable Debate by Quantifying the Robustness of Inferences The Selection of Interaction Partners Estimation of Selection Models Quantifying the Robustness of Inferences from Selection Models Discussion Conclusion Notes References Part III: Netwrok Dimensions Chapter 16: Case Studies in Network Community Detection Virality Prediction of Social Memes Congressional Roll Call Exploratory Analysis of the C. Elegans Neural Network Comparing Network Architectures of the Human Brain at Different States A Probabilistic Network Model for Malaria Parasite Genes Concluding Comments Acknowledgments References Chapter 17: Three Perspectiveson Centrality The Walk Structure Perspective The Contribution/Induced Centrality Perspective The Flow Outcomes Perspective Discussion Final Note Acknowledgments Notes References Chapter 18: Network Visualization Brief History and Motivations Basic Network Visualization Strategies: Better Sociograms Advanced Network Visualization Approaches: Moving beyond Sociograms Conclusions A Note on Software References Chapter 19: The Spatial Dimensions of Social Networks Micro-Level Networks of People Meso-Level Networks of Things Macro-Level Networks of Places Networks in Latent Space Frontiers Notes References Chapter 20: Field Experiments of Preferential Attachment A Novel Application: http://www.ebay.com Acknowledgment Notes References Chapter 21: Duality beyond Persons and Groups: Culture and Affiliation Duality in Past and Present Sociology Limitations of Breiger’s 1974 Formulation Scope of Duality Discussion Dualities in the Analysis of Culture Dualities of Artists and Art Worlds Duality of Actors and Cultural Forms Dualities of Networks and Meaning From Relationality to “Fusion” of Networks and Culture Dualities in the Analysis of Structures: Affiliation Networks Affiliation Networks Revamping Old Ideas? “New” Science of Networks Actor-Network Theory and “Heterogeneous Networks” Recent Developments and Future Directions Duality and Its Extensions toward Multiple Networks Cultural Analysis: Duality of Documents and Words Yielding Categories Notes References Chapter 22: Networks of Culture, Networks of Meaning Two Approaches to Text Networks What Does Meaning Mean? Network Text Analysis for Meaning Structure Constructing Text Networks Results Computational Narrative Analysis for Embedded Meaning Constructing Subject-Action-Object Networks Results Conclusion Acknowledgment Note References Chapter 23: Historical Network Research Cross-Cutting Ties Informal Social Ties Associational and Organizational Networks Narrative Networks Cohesion Brokerage and Centrality Conclusions References Part IV: Network Landscape Chapter 24: Networks in Archaeology The Added Value of the “Network”? Dyads and Triads Encounters with Network Thinking in Archaeology Spatial Network Analysis and “Theory Models” From Theory Models to Data Models Entangled Networks of Humans and Things Acknowledgments Notes References Chapter 25: Networks, Kin, and Social Support Size Density Betweenness Transitivity Reciprocity Embeddedness Families as Systems of Exchanges Defining Family Roles through Configurations of Interactions Caring Roles Affectionate Roles Limited Interaction Roles Entwined Lives Roles Friendly Roles References Chapter 26: Demography and Networks Demography: Enumeration, Estimation, and Explanation Network Approaches and Current Contributions to Demography Future Directions for Network Approaches to Advance Demographic Research Note References Chapter 27: The Neuroscience of Social Networks The Neuroscience of Social Networks Fields Collide: The Social Brain Hypothesis An Emerging New Field Why the Brain? How the Brain Encodes Social Relationships Differential Neural Responses to Friends and Strangers The Need to Move beyond “Friend versus Stranger” The Neural Representation of Social Closeness The Neural Encoding of Indirect Social Relationships The Importance of Indirect Social Relationships to Everyday Human Thought and Behavior The Neural Encoding of Social Network Position Characteristics Distinct but Analogous Facets of Social Status How the Brain Shapes and Constrains Social Networks Does the Processing Capacity of the Human Brain Constrain Social Network Size? How Social Networks Shape the Brain Summary References Chapter 28: Computational Social Science, Big Data, and Networks Computational Thinking about Social Processes Challenges in Modeling Social Data Machine Learning and Social Sciences Online Experimentation on Interactions Online Field Experiments Challenges Notes References Chapter 29: Networks: An Economic Perspective Why Should We Study NetworkStructure? Externalities: A Unifying Theme Overview Network Formation Behavior and Games on Networks Strategic Complementarities Financial Networks Social Learning Labor Markets Development Economics Exchange Theory, Bargaining, and Trade on Networks Empirical Analyses of Network Models Concluding Remarks Notes References Chapter 30: Social Capital and Economic Sociology Social Capital and the Labor Market Job-Matching Processes Job-Matching Outcomes Social Capital and Workplace Outcomes Antecedents Individual Performance and Innovation Outcomes Trust and Collective Outcomes Power and Influence Summary References Chapter 31: The International Trade Network Data and Measurement in ITN Studies World System Classification in the ITN Topological Properties of the ITN Explaining the ITN Effect of Homophily on the ITN Effect of Systemic Equivalence on the ITN Effect of Topological Properties on the ITN Multivariate Regression Quadratic Assignment Procedure A Future Direction: Exponential Random Graph Model References Chapter 32: Maps of Science, Technology, and Education Map Design Map Utility Exemplary Maps of Science, Technology, and Education Springer Nature SciGraph NSF Graph Tool DIA2 NIH CTSA Expertise Explorer NIH Twitter Activity Explorer Learning LeX Subway Maps CyberSeek Career Maps Discussion and Outlook Scalable, Multilevel Maps Acknowledgments Notes References Chapter 33: Criminal Networks Criminal Networks Measuring Criminal Groups and Groups of Criminals Criminal Groups Co-Offending Groups Criminal Investigations Criminal Network Data Theoretical Foundations in Criminal Networks Organizations Diffusion Group Process Criminal Justice Applications Moving Criminal Networks Forward Notes References Index While some social scientists may argue that we have always been networked, the increased visibility of networks today across economic, political, and social domains can hardly be disputed. Social networks fundamentally shape our lives and social network analysis has become a vibrant, interdisciplinary field of research. In The Oxford Handbook of Social Networks , Ryan Light and James Moody have gathered forty leading scholars in sociology, archaeology, economics, statistics, and information science, among others, to provide an overview of the theory, methods, and contributions in the field of social networks. Each of the thirty-three chapters in this Handbook moves through the basics of social network analysis aimed at those seeking an introduction to advanced and novel approaches to modeling social networks statistically. They cover both a succinct background to, and future directions for, distinctive approaches to analyzing social networks. The first section of the volume consists of theoretical and methodological approaches to social networks, such as visualization and network analysis, statistical approaches to networks, and network dynamics. Chapters in the second section outline how network perspectives have contributed substantively across numerous fields, including public health, political analysis, and organizational studies. Despite the rapid spread of interest in social network analysis, few volumes capture the state-of-the-art theory, methods, and substantive contributions featured in this volume. This Handbook therefore offers a valuable resource for graduate students and faculty new to networks looking to learn new approaches, scholars interested in an overview of the field, and network analysts looking to expand their skills or substantive areas of research. While some social scientists may argue that we have always been networked, the increased visibility of networks today across economic, political, and social domains can hardly be disputed. Social networks fundamentally shape our lives and social network analysis has become a vibrant, interdisciplinary field of research. In this handbook, Ryan Light and James Moody have gathered 40 leading scholars in sociology, archaeology, economics, statistics, and information science, among others, to provide an overview of the theory, methods, and contributions in the field of social networks. Each of the chapters moves through the basics of social network analysis aimed at those seeking an introduction to advanced and novel approaches to modeling social networks statistically