Stanley Wasserman

Indiana University Bloomington

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Katherine Faust

University of California, Irvine

Ulrik Brandes

ETH Zurich

Dawn Iacobucci

Vanderbilt University

Alessandro Vespignani

Institute for Scientific Interchange

Garry Robins

University of Melbourne

Thomas W. Valente

University of Southern California

Filippo Menczer

Indiana University Bloomington

Ronald L. Breiger

University of Arizona

Douglas Steinley

University of Missouri

Joseph Galaskiewicz

University of Arizona

Cooperative Institutions

University of Illinois Urbana-Champaign

Northwestern University

Indiana University

University of Michigan–Ann Arbor

University of Minnesota

National Research University Higher School of Economics

University of California, Berkeley

University of Southern California

Carnegie Mellon University

University of Cambridge

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Computer Programs

Stanley Wasserman Katherine Faust

A summary is not available for this content so a preview has been provided. Please use the Get access link above for information on how to access this content.

Content (measure theory)

10.1017/cbo9780511815478.019

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NWS volume 4 issue 4 Cover and Back matter

Network Science (2016)

Ulrik Brandes Ronald L. Breiger Filippo Menczer Jaideep Srivastava Thomas W. Valente

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10.1017/nws.2016.30

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NWS volume 3 issue 4 Cover and Back matter

Network Science (2015)

Ulrik Brandes Filippo Menczer Garry Robins Jaideep Srivastava Thomas W. Valente

An abstract is not available for this content so a preview has been provided. As you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

10.1017/nws.2015.41

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Conformity of two sociometric relations

Psychometrika (1987)

Stanley Wasserman

Conformity

Popularity

Reciprocity

10.1007/bf02293953

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Citations (52)

Structural Balance and Transitivity

Cambridge University Press eBooks (1994)

Stanley Wasserman Katherine Faust

One of the most important concepts to emerge from the early days of social network analysis was balance theory. The early focus in balance theory was on the cognition or awareness of sociometric relations, usually positive and negative affect relations such as friendship, liking, or disliking, from the perspective of an individual.

Balance theory

Affect

10.1017/cbo9780511815478.007

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Citations (4)

Social support and social networks: synthesis and review

Advances in medical sociology (2005)

Ashley D. Faber Stanley Wasserman

Social network analysis is a collection of methodological tools that provide a variety of measures and models for describing relationships among social actors embedded in networks of social support. Although methodologists have made great advancements in the area of statistical models for networks, little social support research has moved beyond descriptive measurements of network data. Here we review selected social support literature that has begun to utilize a greater variety of network analyses. We describe and synthesize this literature, then discuss other quantitative tools of use in describing and studying support networks. We also review recent developments in theoretical and applied social support research including research on the role of support networks for persons with HIV/AIDS and older adults. We conclude by discussing the most recently developed statistical models for networks, highlighting their use in a variety of contexts.

Social Network Analysis

Social network (sociolinguistics)

10.1016/s1057-6290(02)80020-1

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Citations (93)

Random directed graph distributions and the triad census in social networks†

Journal of Mathematical Sociology (1977)

Stanley Wasserman

This paper uses the concept of the triad census as, developed by Holland and Leinhardt, and describes several distributions on directed graphs. Methods are presented for calculating the mean and the covariance matrix of the triad census for the uniform distribution that conditions on the number of choices made by each individual in the social network. Several complex distributions on digraphs are approximated, and an application of these methods to a sociogram is given.

Triad (sociology)

Social network (sociolinguistics)

10.1080/0022250x.1977.9989865

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Citations (67)

Introduction to the special issue on COMPLEX NETWORKS 2018

Network Science (2020)

Hocine Cherifi Luís M. Rocha Stanley Wasserman

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10.1017/nws.2020.22

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Book Reviews

CHANCE (1999)

Stanley Wasserman

Abstract Markov Chain Monte Carlo in Practice by W. R. Gilks, S. Richardson, and D. J. Spiegelhalter, New York: Chapman & Hall, 1996, 486 pp. Reviewed by John W. McDonald

10.1080/09332480.1999.10542134

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Statistical Analysis of Single Relational Networks

Cambridge University Press eBooks (1994)

Stanley Wasserman Katherine Faust

We now turn our attention to stochastic models for social network data. The methodology described here continues the development of statistical methods for network data begun in Chapter 13. We begin in Chapter 15 by considering a (very special) class of statistical distributions for random directed graphs, which, as we will show, is a special case of the uniform random directed graph distributions presented in Chapter 13. This class is more interesting than the distributions of Chapter 13, and contains substantively meaningful parameters which reflect a wide variety of graph properties. Further, the parameters can actually be estimated from data. The basic model has many generalizations and extensions, some of which are described in Chapter 16.

Statistical Analysis

10.1017/cbo9780511815478.016

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Citations (2)