Social Network Analysis : Methods and Applications (Structural Analysis in the Social Sciences, 8)

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Social Network Analysis : Methods and Applications (Structural Analysis in the Social Sciences, 8)

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  • 製本 Paperback:紙装版/ペーパーバック版/ページ数 780 p.
  • 言語 ENG
  • 商品コード 9780521387071
  • DDC分類 302.011

Full Description


Social network analysis is used widely in the social and behavioral sciences, as well as in economics, marketing, and industrial engineering. The social network perspective focuses on relationships among social entities and is an important addition to standard social and behavioral research, which is primarily concerned with attributes of the social units. Social Network Analysis: Methods and Applications reviews and discusses methods for the analysis of social networks with a focus on applications of these methods to many substantive examples. It is a reference book that can be used by those who want a comprehensive review of network methods, or by researchers who have gathered network data and want to find the most appropriate method by which to analyze it. It is also intended for use as a textbook as it is the first book to provide comprehensive coverage of the methodology and applications of the field.

Table of Contents

        List of Tables                             xxi
List of Illustrations xxiv
Preface xxix
Part I: Networks, Relations, and Structure 1 (66)
Social Network Analysis in the Social and 3 (25)
Behavioral Sciences
The Social Networks Perspective 4 (6)
Historical and Theoretical Foundations 10 (7)
Empirical Motivations 11 (2)
Theoretical Motivations 13 (2)
Mathematical Motivations 15 (1)
In Summary 16 (1)
Fundamental Concepts in Network Analysis 17 (4)
Distinctive Features 21 (1)
Organization of the Book and How to Read It 22 (5)
Complexity 23 (1)
Descriptive and Statistical Methods 23 (1)
Theory Driven Methods 24 (1)
Chronology 24 (1)
Levels of Analysis 25 (1)
Chapter Prerequisites 26 (1)
Summary 27 (1)
Social Network Data 28 (39)
Introduction: What Are Network Data? 28 (2)
Structural and Composition Variables 29 (1)
Modes 29 (1)
Affiliation Variables 30 (1)
Boundary Specification and Sampling 30 (5)
What Is Your Population? 31 (2)
Sampling 33 (2)
Types of Networks 35 (8)
One-Mode Networks 36 (3)
Two-Mode Networks 39 (2)
Ego-centered and Special Dyadic Networks 41 (2)
Network Data, Measurement and Collection 43 (16)
Measurement 43 (2)
Collection 45 (10)
Longitudinal Data Collection 55 (1)
Measurement Validity, Reliability, 56 (3)
Accuracy, Error
Data Sets Found in These Pages 59 (8)
Krackhardt's High-tech Managers 60 (1)
Padgett's Florentine Families 61 (1)
Freeman's EIES Network 62 (2)
Countries Trade Data 64 (1)
Galaskiewicz's CEOs and Clubs Network 65 (1)
Other Data 66 (1)
Part II: Mathematical Representations of Social 67 (100)
Networks
Notation for Social Network Data 69 (23)
Graph Theoretic Notation 71 (6)
A Single Relation 71 (2)
xcirc;Multiple Relations 73 (2)
Summary 75 (2)
Sociometric Notation 77 (7)
Single Relation 79 (2)
Multiple Relations 81 (2)
Summary 83 (1)
◯Algebraic Notation 84 (1)
◯Two Sets of Actors 85 (4)
&otime;Different Types of Pairs 86 (1)
◯Sociometric Notation 87 (2)
Putting It All Together 89 (3)
Graphs and Matrices 92 (75)
Why Graphs? 93 (1)
Graphs 94 (27)
Subgraphs, Dyads, and Triads 97 (3)
Nodal Degree 100 (1)
Density of Graphs and Subgraphs 101 (2)
Example: Padgett's Florentine Families 103 (2)
Walks, Trails, and Paths 105 (4)
Connected Graphs and Components 109 (1)
Geodesics, Distance, and Diameter 110 (2)
Connectivity of Graphs 112 (5)
Isomorphic Graphs and Subgraphs 117 (2)
◯Special Kinds of Graphs 119 (2)
Directed Graphs 121 (15)
Subgraphs - Dyads 124 (1)
Nodal Indegree and Outdegree 125 (4)
Density of a Directed Graph 129 (1)
An Example 129 (1)
Directed Walks, Paths, Semipaths 129 (3)
Reachability and Connectivity in Digraphs 132 (2)
Geodesics, Distance and Diameter 134 (1)
◯Special Kinds of Directed Graphs 134 (2)
Summary 136 (1)
Signed Graphs and Signed Directed Graphs 136 (4)
Signed Graph 137 (1)
Signed Directed Graphs 138 (2)
Valued Graphs and Valued Directed Graphs 140 (5)
Nodes and Dyads 142 (1)
Density in a Valued Graph 143 (1)
◯Paths in Valued Graphs 143 (2)
Multigraphs 145 (1)
&otime;Hypergraphs 146 (2)
Relations 148 (2)
Definition 148 (1)
Properties of Relations 149 (1)
Matrices 150 (14)
Matrices for Graphs 150 (2)
Matrices for Digraphs 152 (1)
Matrices for Valued Graphs 153 (1)
Matrices for Two-Mode Networks 154 (1)
ôMatrices for Hypergraphs 154 (1)
Basic Matrix Operations 154 (5)
Computing Simple Network Properties 159 (5)
Summary 164 (1)
Properties 164 (1)
Reflexivity 164 (1)
Symmetry 165 (1)
Transitivity 165 (1)
Summary 165 (2)
Part III: Structural and Locational Properties 167 (178)
Centrality and Prestige 169 (51)
Prominence: Centrality and Prestige 172 (5)
Actor Centrality 173 (1)
Actor Prestige 174 (1)
Group Centralization and Group Prestige 175 (2)
Nondirectional Relations 177 (21)
Degree Centrality 178 (5)
Closeness Centrality 183 (5)
Betweenness Centrality 188 (4)
&otime;Information Centrality 192 (6)
Directional Relations 198 (17)
Centrality 199 (3)
Prestige 202 (8)
A Different Example 210 (5)
Comparisons and Extensions 215 (5)
Structural Balance and Transitivity 220 (29)
Structural Balance 222 (11)
Signed Nondirectional Relations 223 (5)
Signed Directional Relations 228 (2)
◯Checking for Balance 230 (2)
An Index for Balance 232 (1)
Summary 232 (1)
Clusterability 233 (6)
The Clustering Theorems 235 (3)
Summary 238 (1)
Generalizations of Clusterability 239 (4)
Empirical Evidence 239 (1)
◯Ranked Clusterability 240 (2)
Summary 242 (1)
Transitivity 243 (4)
Conclusion 247 (2)
Cohesive Subgroups 249 (42)
Background 250 (3)
Social Group and Subgroup 250 (2)
Notation 252 (1)
Subgroups Based on Complete Mutuality 253 (4)
Definition of a Clique 254 (1)
An Example 254 (2)
Considerations 256 (1)
Reachability and Diameter 257 (6)
n-cliques 258 (1)
An Example 259 (1)
Considerations 260 (1)
n-clans and n-clubs 260 (2)
Summary 262 (1)
Subgroups Based on Nodal Degree 263 (4)
k-plexes 265 (1)
k-cores 266 (1)
Comparing within to Outside Subgroup Ties 267 (3)
LS Sets 268 (1)
Lambda Sets 269 (1)
Measures of Subgroup Cohesion 270 (3)
Directional Relations 273 (4)
Cliques Based on Reciprocated Ties 273 (1)
Connectivity in Directional Relations 274 (1)
n-cliques in Directional Relations 275 (2)
Valued Relations 277 (6)
Cliques, n-cliques, and k-plexes 278 (4)
Other Approaches for Valued Relations 282 (1)
Interpretation of Cohesive Subgroups 283 (1)
Other Approaches 284 (6)
Matrix Permutation Approaches 284 (3)
Multidimensional Scaling 287 (3)
◯Factor Analysis 290 (1)
Summary 290 (1)
Affiliations and Overlapping Subgroups 291 (54)
Affiliation Networks 291 (1)
Background 292 (6)
Theory 292 (2)
Concepts 294 (1)
Applications and Rationale 295 (3)
Representing Affiliation Networks 298 (9)
The Affiliation Network Matrix 298 (1)
Bipartite Graph 299 (4)
Hypergraph 303 (3)
◯Simplices and Simplicial Complexes 306 (1)
Summary 306 (1)
An example: Galaskiewicz's CEOs and Clubs 307 (1)
One-mode Networks 307 (5)
Definition 307 (2)
Examples 309 (3)
Properties of Affiliation Networks 312 (14)
Properties of Actors and Events 312 (2)
Properties of One-mode Networks 314 (8)
Taking Account of Subgroup Size 322 (2)
Interpretation 324 (2)
&otime;Analysis of Actors and Events 326 (16)
&otime;Galois Lattices 326 (8)
&otime;Correspondence Analysis 334 (8)
Summary 342 (3)
Part IV: Roles and Positions 345 (158)
Structural Equivalence 347 (47)
Background 348 (8)
Social Roles and Positions 348 (3)
An Overview of Positional and Role 351 (3)
Analysis
A Brief History 354 (2)
Definition of Structural Equivalence 356 (5)
Definition 356 (1)
An Example 357 (2)
Some Issues in Defining Structural 359 (2)
Equivalence
Positional Analysis 361 (5)
Simplification of Multirelational Networks 361 (2)
Tasks in a Positional Analysis 363 (3)
Measuring Structural Equivalence 366 (9)
Euclidean Distance as a Measure of 367 (1)
Structural Equivalence
Correlation as a Measure of Structural 368 (2)
Equivalence
Some Considerations in Measuring 370 (5)
Structural Equivalence
Representation of Network Positions 375 (16)
Partitioning Actors 375 (10)
Spatial Representations of Actor 385 (3)
Equivalences
Ties Between and Within Positions 388 (3)
Summary 391 (3)
Blockmodels 394 (31)
Definition 395 (2)
Building Blocks 397 (11)
Perfect Fit (Fat Fit) 398 (1)
Zeroblock (Lean Fit) Criterion 399 (1)
Oneblock Criterion 400 (1)
α Density Criterion 400 (1)
Comparison of Criteria 401 (1)
Examples 401 (5)
Valued Relations 406 (2)
Interpretation 408 (15)
Actor Attributes 408 (3)
Describing Individual Positions 411 (6)
Image Matrices 417 (6)
Summary 423 (2)
Relational Algebras 425 (36)
Background 426 (2)
Notation and Algebraic Operations 428 (5)
Composition and Compound Relations 429 (3)
Properties of Composition and Compound 432 (1)
Relations
Multiplication Tables for Relations 433 (9)
Multiplication Tables and Relational 435 (4)
Structures
An Example 439 (3)
Simplification of Role Tables 442 (7)
Simplification by Comparing Images 443 (2)
&otime;Homomorphic Reduction 445 (4)
&otime;Comparing Role Structures 449 (11)
Joint Homomorphic Reduction 451 (1)
The Common Structure Semigroup 452 (1)
An Example 453 (4)
Measuring the Similarity of Role 457 (3)
Structures
Summary 460 (1)
Network Positions and Roles 461 (42)
Background 462 (6)
Theoretical Definitions of Roles and 462 (2)
Positions
Levels of Role Analysis in Social Networks 464 (2)
Equivalences in Networks 466 (2)
Structural Equivalence, Revisited 468 (1)
Automorphic and Isomorphic Equivalence 469 (4)
Definition 470 (1)
Example 471 (1)
Measuring Automorphic Equivalence 472 (1)
Regular Equivalence 473 (10)
Definition of Regular Equivalence 474 (1)
Regular Equivalence for Nondirectional 475 (1)
Relations
Regular Equivalence Blockmodels 476 (3)
◯A Measure of Regular Equivalence 479 (2)
An Example 481 (2)
``Types'' of Ties 483 (4)
An Example 485 (2)
Local Role Equivalence 487 (7)
Measuring Local Role Dissimilarity 488 (3)
Examples 491 (3)
&otime;Ego Algebras 494 (8)
Definition of Ego Algebras 496 (1)
Equivalence of Ego Algebras 497 (1)
Measuring Ego Algebra Similarity 497 (2)
Examples 499 (3)
Discussion 502 (1)
Part V: Dyadic and Triadic Methods 503 (100)
Dyads 505 (51)
An Overview 506 (2)
An Example and Some Definitions 508 (2)
Dyads 510 (12)
The Dyad Census 512 (1)
The Example and Its Dyad Census 513 (1)
An Index for Mutuality 514 (4)
&otime;A Second Index for Mutuality 518 (2)
◯Subgraph Analysis, in General 520 (2)
Simple Distributions 522 (6)
The Uniform Distribution - A Review 524 (2)
Simple Distributions on Digraphs 526 (2)
Statistical Analysis of the Number of Arcs 528 (7)
Testing 529 (4)
Estimation 533 (2)
&otime;Conditional Uniform Distributions 535 (4)
Uniform Distribution, Conditional on the 536 (1)
Number of Arcs
Uniform Distribution, Conditional on the 537 (2)
Outdegrees
Statistical Analysis of the Number of 539 (5)
Mutuals
Estimation 540 (2)
Testing 542 (1)
Examples 543 (1)
&otime;Other Conditional Uniform 544 (8)
Distributions
Uniform Distribution, Conditional on the 545 (2)
Indegrees
The U\MAN Distribution 547 (3)
More Complex Distributions 550 (2)
Other Research 552 (3)
Conclusion 555 (1)
Triads 556 (47)
Random Models and Substantive Hypotheses 558 (1)
Triads 559 (16)
The Triad Census 564 (10)
The Example and Its Triad Census 574 (1)
Distribution of a Triad Census 575 (10)
&otime;Mean and Variance of a k-subgraph 576 (3)
Census
Mean and Variance of a Triad Census 579 (2)
Return to the Example 581 (1)
Mean and Variance of Linear Combinations 582 (2)
of a Triad Census
A Brief Review 584 (1)
Testing Structural Hypotheses 585 (13)
Configurations 585 (5)
From Configurations to Weighting Vectors 590 (2)
From Weighting Vectors to Test Statistics 592 (3)
An Example 595 (1)
Another Example --- Testing for 596 (2)
Transitivity
Generalizations and Conclusions 598 (3)
Summary 601 (2)
Part VI: Statistical Dyadic Interaction Models 603 (122)
Statistical Analysis of Single Relational 605 (70)
Networks
Single Directional Relations 607 (28)
The Y-array 608 (4)
Modeling the Y-array 612 (7)
Parameters 619 (14)
&otime;Is p1 a Random Directed Graph 633 (1)
Distribution?
Summary 634 (1)
Attribute Variables 635 (14)
Introduction 636 (1)
The W-array 637 (3)
The Basic Model with Attribute Variables 640 (6)
Examples: Using Attribute Variables 646 (3)
Related Models for Further Aggregated Data 649 (7)
Strict Relational Analysis --- The V-array 651 (3)
Ordinal Relational Data 654 (2)
◯Nondirectional Relations 656 (2)
A Model 656 (1)
An Example 657 (1)
&otime;Recent Generalizations of p1 658 (4)
&otime;Single Relations and Two Sets of 662 (3)
Actors
Introduction 662 (1)
The Basic Model 663 (1)
Aggregating Dyads for Two-mode Networks 664 (1)
Computing for Log-linear Models 665 (8)
Computing Packages 666 (5)
From Printouts to Parameters 671 (2)
Summary 673 (2)
Stochastic Blockmodels and Goodness-of-Fit 675 (50)
Indices
Evaluating Blockmodels 678 (14)
Goodness-of-Fit Statistics for Blockmodels 679 (9)
Structurally Based Blockmodels and 688 (1)
Permutation Tests
An Example 689 (3)
Stochastic Blockmodels 692 (27)
Definition of a Stochastic Blockmodel 694 (2)
Definition of Stochastic Equivalence 696 (1)
Application to Special Probability 697 (6)
Functions
Goodness-of-Fit Indices for Stochastic 703 (3)
Blockmodels
◯Stochastic a posteriori Blockmodels 706 (2)
Measures of Stochastic Equivalence 708 (1)
Stochastic Blockmodel Representations 709 (3)
The Example Continued 712 (7)
Summary: Generalizations and Extensions 719 (6)
Statistical Analysis of Multiple 719 (2)
Relational Networks
Statistical Analysis of Longitudinal 721 (4)
Relations
Part VII: Epilogue 725 (10)
Future Directions 727 (8)
Statistical Models 727 (2)
Generalizing to New Kinds of Data 729 (2)
Multiple Relations 730 (1)
Dynamic and Longitudinal Network Models 730 (1)
Ego-centered Networks 731 (1)
Data Collection 731 (1)
Sampling 732 (1)
General Propositions about Structure 732 (1)
Computer Technology 733 (1)
Networks and Standard Social and Behavioral 733 (2)
Science
Appendix A Computer Programs 735 (3)
Appendix B Data 738 (18)
References 756 (46)
Name Index 802 (9)
Subject Index 811 (8)
List of Notation 819