# Stan WassermanIndiana University Bloomington | IUB

Stan Wasserman

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95

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Introduction

**Skills and Expertise**

## Publications

Publications (95)

Introduction to the special issue on COMPLEX NETWORKS 2018 - Volume 8 Issue S1 - Hocine Cherifi, Luis M. Rocha, Stanley Wasserman

During the last century, networks of several types have been used to model a wide range of physical, biological and social systems. For example, Moreno (1934) studied social networks with multiple types of ties, later called multiplex networks (Verbrugge, 1979; Minor, 1983; Lazega & Pattison, 1999) as well as networks with multiple types of actors....

Social actors are often nested within multiple levels that share several members, giving rise to multimodal data. Such data are complex if the actor-nesting is not mutually exclusive. We use affiliation networks to represent teams and individuals, with links representing team membership; social relations between individuals are represented using on...

Recent developments in statistical models for social networks reflect an increasing theoretical focus in the social and behavioral sciences on the interdependence of social actors in dynamic, network-based social settings. As a result, a growing importance has been accorded the problem of modeling the dynamic and complex interdependencies among net...

The special issue of “Networks in space and in time: methods and applications” contributes
to the debate on contextual analysis in network science. It includes seven research papers that
shed light on the analysis of network phenomena studied within geographic space and across
temporal dimensions. In these papers, methodological issues as well as s...

Thank you for the support in getting Network Science up and running. We are deeply appreciative of the work our associate editors, authors, and reviewers have put into realizing this vision of an interdisciplinary journal for network science. And of course, the journal would not be possible without the hard work of the editors of Network Science, w...

This is the beginning of Network Science. The journal has been created because network science is exploding. As is typical for a field in formation, the discussions about its scope, contents, and foundations are intense. On these first few pages of the first issue of our new journal, we would like to share our own vision of the emerging science of...

This is the last of two separate entries under the broad topic Social network analysis. This entry includes the following topics: ego-centered networks and social support; social cognition; organizations and networks; methods. (PsycINFO Database Record (c) 2012 APA, all rights reserved)

Latent variable models are frequently used to identify structure in dichotomous network data, in part, because they give rise to a Bernoulli product likelihood that is both well understood and consistent with the notion of exchangeable random graphs. ...

Clusterwise p* models are developed to detect differentially functioning network models as a function of the subset of observations being considered. These models allow the identification of subgroups (i.e., clusters) of individuals who are ‘structurally’ different from each other. These clusters are different from those produced by standard blockm...

I enrolled in the Graduate School of Arts and Sciences at Harvard in fall 1973 to do graduate work in statistics. I had six classmates in my cohort, four of whom eventually received PhDs. One, Richard Hill, a recent graduate of MIT, was also an administrator at the Computer Research Center (CRC) of the National Bureau Economic Research (NBER). He w...

Data mining of network data often focuses on classification methods from machine learning, statistics, and pattern recognition perspectives. These techniques have been described by many, but many of these researchers are unaware of the rich history of classification and clustering techniques originating in social network analysis. The growth of ric...

Network science focuses on relationships between social entities. It is used widely in the social and behavioral sciences, as well as in political science, economics, organizational science, and industrial engineering. The social network perspective has been developed over the last sixty years by researchers in psychology, sociology, and anthropolo...

We begin with a graph (or a directed graph), a single set of nodes
N\mathcal{N}
, and a set of lines or arcs
L\mathcal{L}
. It is common to use this mathematical concept to represent a network. We use the notation of [1], especially Chapters 13
and 15. There are extensions of these ideas to a wide range of networks, including multiple relations,...

The authors use p* modeling to explore connections between network structures and social influence in a seventh-grade friendship network. Specifically, p* parameters reveal how bullying perpetration, dyads, triads, and more complex group structures contribute to network formation, providing fine-level detail about the operation of internal peer gro...

Sounds emitted by eighteen foods were positioned in one- and two-dimensional spaces by the nonmetric multidimensional scaling (MDS) algorithm MINISSA. Each of the eighteen food sounds was also scored on 15 sensory acoustical quality attributes. These sensory quality data were then used to study and interpret the MDS graphical representation. The re...

Date revised - 20080324, Language of summary - English, Number of references - 63, Pages - 450-464, ProQuest ID - 621893704, Address - No recipient indicated, PubXState - NY, SubjectsTermNotLitGenreText - 221 7631 853; 4384 3306 7657; 5964 4232 7662 7631 853; 7673; 8699 518 853 1774 4232 7662 7631 221; 371; 7660, Target audience - Psychology: Profe...

Network forms of organization, unlike hierarchies or marketplaces, are agile and are constantly adapting as new links are added and dysfunctional ones dropped. We review some of the theoretical and methodological accomplishments and challenges of contemporary research on organizational networks. We then offer an analytic framework that can be used...

Network analysis is the interdisciplinary study of social relations and has roots in anthropology, sociology, psychology, and applied mathematics. It conceives of social structure in relational terms, and its most fundamental construct is that of a social network, comprising at the most basic level a set of social actors and a set of relational tie...

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 de...

A multirelational social network on a set of individuals may be represented as a collection of binary relations. Compound relations constructed from this collection represent various labeled paths linking individuals in the network. Since many models of interest for social networks can be formulated in terms of orderings among these labeled paths,...

Recent developments in statistical models for social networks reflect an increasing theoretical focus in the social and behavioral sciences on the interdependence of social actors in dynamic, network-based social settings (e.g., Abbott, 1997; White, 1992, 1995). As a result, a growing importance has been accorded the problem of modeling the dynamic...

Preface. Measurement and Repeated Observations of Categorical Data: D. Andrich, Measurement Criteria for Choosing Among Models with Graded Responses. B.O. Muthn, Growth Modeling with Binary Responses. G. Arminger, Probit Models for the Analysis of Limited-Dependent Panel Data. Catastrophe Theory: H.L.J. van der Maas and P.C.M. Molenaar, Catastrophe...

The research described here builds on our previous work by generalizing the univariate models described there to models for multivariate relations. This family, labelled p*, generalizes the Markov random graphs of Frank and Strauss, which were further developed by them and others, building on Besag's ideas on estimation. These models were first use...

This paper generalizes the p * model for dichotomous social network data (Wasserman & Pattison, 1996) to the polytomous case. The generalization is achieved by transforming valued social networks into three-way binary arrays. This data transformation requires a modification of the Hammersley-Clifford theorem that underpins the p * class of models....

A major criticism of the statistical models for analyzing social networks developed by Holland, Leinhardt, and others [Holland, P.W., Leinhardt, S., 1977. Notes on the statistical analysis of social network data; Holland, P.W., Leinhardt, S., 1981. An exponential family of probability distributions for directed graphs. Journal of the American Stati...

This article examines several factors that are hypothesized to influence the perceptual congruence among organizational members. Perceptual congruence is defined as the extent to which members agree on their perceptions of the organization's social structure. This study proposes that employees congruence on the organization's social structure is in...

Spanning nearly sixty years of research, statistical network analysis has passed through (at least) two generations of researchers and models. Beginning in the late 1930's, the first generation of research dealt with the distribution of various network statistics, under a variety of null models. The second generation, beginning in the 1970's and co...

The methodology described here is designed for social networks and is based on the research of Holland and Leinhardt, Wasserman and Iacobucci, and many others. Holland and Leinhardt termed the simplest model form their family of log-linear models pt. The models presented in this article are not log-linear-rather they are log-multiplicative, in the...

In this paper we discuss the construction and fitting of structural models for local, or ego-centered, social networks. We define partial algebraic structures from the collection of network paths having a focal individual as their source. Such structures are constrained in part by different methods of local network data collection. We present a sta...

Network analysis has been used extensively in sociology over the last twenty years. This special issue of Sociological Methods & Research reviews the substantive contributions that network analysis has made to five areas: political sociology, interorganizational relations, social support, social influence, and epidemiology. To introduce the novice...

In recent years, the conceptualization of social support in the literature has become increasingly sophisticated, facilitating the consideration of more complex theories. Researchers no longer consider the mere availability of social ties, but look instead at the flow of specific resources through a social network. This article discusses how the so...

Alan Agresti is a Professor of Statistics at the University of Florida. He obtained his Ph.D. in Statistics at the University of Wisconsin and is a Fellow of the American Statistical Association. Thomas Wickens is a Professor of Psychology at the University of California Los Angeles. He obtained his Ph.D. in Psychology at Brown University.Carolyn A...

Part I. Introduction: Networks, Relations, and Structure: 1. Relations and networks in the social and behavioral sciences 2. Social network data: collection and application Part II. Mathematical Representations of Social Networks: 3. Notation 4. Graphs and matrixes Part III. Structural and Locational Properties: 5. Centrality, prestige, and related...

This paper describes and illustrates correlation models (correspondence analysis and canonical correlation analysis) and association models for studying the order and spacing of categories of ordinal relational variables. Both correlation models and association models study departures from independence in two-way contingency tables. One result of f...

Many methods for the description of social network structural properties are concerned with the dual notions of social position and social role. Common goals of these methods are to represent patterns in complex social network data in simplified form, to reveal sets of actors who are similarly embedded in networks of relations, and to describe the...

The literature devoted to the construction of stochastic blockmodels is relatively rare compared to that of the deterministic variety. In this paper, a general definition of a stochastic blockmodel is given and a number of techniques for building such blockmodels are presented. In the statistical approach, the likelihood ratio statistic provides a...

The abstract for this document is available on CSA Illumina.To view the Abstract, click the Abstract button above the document title.

A common problem in data analysis occurs when one has many models to compare to a single or just a few data sets. For example, a researcher may conduct an experiment in which subjects respond by choosing one category from a small set of categories. The data set then consists of the frequencies with which the categories occur. Many substantive model...

A bipartite graph, in which the nodes (or actors in a social network) are partitioned into two sets, can be studied using recent statistical models for dyadic interactions. These models, which are loglinear for the probabilities of dyadic choices or interactions, allow not only arcs or relationships to exist between the sets but also within the set...

Traditional network research analyzes relational ties within a single group of actors: the models presented in this paper involve relational ties exist beteen two distinct sets of actors. Statistical models for traditional networks in which relations are measured within a group simplify when modeling unidirectional relations measured between groups...

Correspondence analysis, a data analytic technique used to study two‐way cross‐classifications, is applied to social relational data. Such data are frequently termed “sociometric” or “network” data. The method allows one to model forms of relational data and types of empirical relationships not easily analyzed using either standard social network m...

Developing network models that allow for simultaneous analysis of actor attributes and network relational structure provides a challenge for network researchers. Such models would allow one to look at the characteristics of actors and partners in a network and at the patterns of social relations at the same time. In this paper, we show how recent d...

Recent interest in sequential dyadic interactions has motivated researchers to develop methods appropriate for the analysis of such data. After briefly reviewing a series of methodological papers focusing on the analysis of discrete-valued observations, we present a general framework for studying many substantive effects, including dominance and au...

A new method is proposed for the statistical analysis of dyadic social interaction data measured over time. The data to be studied are assumed to be realizations of a social network of a fixed set of actors interacting on a single relation. The method is based on loglinear models for the probabilities for various dyad (or actor pair) states and gen...

Kraemer and Jacklin (1979) proposed a method of analysis of univariate dyadic social interactions or relational data, and Mendoza and Graziano (1982) extended this method to multivariate relations. Their approach is based on an analysis-of-variance-type model that contains parameters characterizing the behavior of actors and partners and their inte...

In 1983, Holland, Laskey, and Leinhardt, using the ideas of Holland and Leinhardt, and Fienberg and Wasserman, introduced the notion of a stochastic blockmodel. The mathematics for stochastic a priori blockmodels, in which exogenous actor attribute data are used to partition actors independently of any statistical analysis of the available relation...

The problem of comparing two sociometric relations or measurements (A and B) recorded in distinct sociomatrices was originally discussed by Katz and Powell in the early 1950's and Hubert and Baker in the late 1970's. The problem is considered again using a probabilistic model designed specifically for discrete-valued network measurements. The model...

We empirically test existing theories on the provision of public goods, in particular air quality, using data on sulfur dioxide (SO2) concentrations from the Global Environment Monitoring Projects for 107 cities in 42 countries from 1971 to 1996. The results are as follows: First, we provide additional support for the claim that the degree of democ...

Social interaction data record the intensity of the relationship, or frequency of interaction, between two individual actors. Recent methods for analysing such data have treated these relational variables as continuous. A more appropriate method, described here, views these dyadic interactions as variables in multidimensional discrete cross-classif...

Binary interaction data, measuring the presence or absence of a relation between pairs of actors in a “dyadic interaction situation,” are commonly gathered to study the social structure of the group of actors. Recent developments have made the statistical analysis of such data statistically easier and more substantively sophisticated. These develop...

The paper seeks to identify the criteria which companies use to select board members and which firms use to select the outside
boards they sit on. Hypotheses were drawn from theories which view corporate interlocks as a strategy of market cooptation
and from theories which argue that board interlocks are based on the prestige of CEOs or the prestig...

A new method was devised to test object permanence in young infants. Five- month-old infants were habituated to a screen that moved back and forth through a 180-degree arc, in the manner of a drawbridge. After infants reached habituation, a box was centered behind the screen. Infants were shown two test events: a possible event and an impossible ev...

Loglinear models are adapted for the analysis of multivariate social networks, a set of sociometric relations among a group of actors. Models that focus on the similarities and differences between the relations and models that concentrate on individual actors are discussed. This approach allows for the partitioning of the actors into blocks or subg...

In 1977, Holland and Leinhardt introduced a new statistical approach to sociometric data analysis. The details of their approach, based on a model termed P1, were published in 1981 in papers by Holland and Leinhardt, and Fienberg and Wasserman. Since then, many researchers have adopted this model, addressing substantive questions that were unanswer...

Historically, the Poisson process has been the “benchmark” model for many stochastic processes. When event counts from a particular process fail to be described adequately by a Poisson distribution, a researcher may turn to generalized Poisson processes to model the empirical data more accurately. Two common generalizations are the (1) heterogeneou...

Retributive penal philosophy calls for punishment of a law violator to be proportional to the seriousness of the crime committed. However, proportionality is an elusive concept and is calculating differently, especially by utilitarians and retributivists. Studies have been conducted with the perception of students, occupational groups, and the gene...

We adapt a class of new stochastic models for social networks to the study of social change in corporate interlock networks. Data on a regional (Minnesota) network are used to verify several descriptive hypotheses drawn from the existing literature concerning interlocking directorates. We conclude that corporations are more likely to make reciproca...

This note discusses and demonstrates methods, both exploratory and con- firmatory, for analysing data from friendship networks collected over time. The focus is on sio~~~asti~ modems for dyadic interaction designed fo quantify the structural effect of reciprocity on arc changes. The networks studied were previously analysed by Hallinan f Social Net...

A multivariate directed graph consists of a set of g nodes, and a family of directed arcs (one for each relation) connecting pairs of nodes. Such multivariate directed graphs provide natural representations for social networks. In this paper, methods to analyse a network of 73 organizations in a Midwest American community linked by three types of r...

This article presents a new methodology for studying a social network of interpersonal relationships, based on stochastic modeling of the changes that occur in the network over time. Specifically, we postulate that these changes can be modeled as a continuous-time Markov chain. The transition rates for the chain are dependent on a small set of para...

An applied statistics and data-analysis course designed for students of public management and policy analysis, but suitable as an introductory graduate-level applied course in other contexts, is discussed. The course, Quantitative Methods for Public Management (QMPM), is a departure from traditional instruction in statistics. It uses subject-matter...

The nature and historical development of both stochastic and deterministic models for binary graphs are discussed. Here the focus of applications is sociological and emphasizes representations of networks of interpersonal relations as directed graphs. Models from the natural sciences and from the social sciences are examined and suggestions for fut...

The nature and historical development of both stochastic and deterministic models for binary graphs are discussed. Here the focus of applications is sociological and emphasizes representations of networks of interpersonal relations as directed graphs. Models from the natural sciences and from the social sciences are examined and suggestions for fut...

The stem-and-leaf display is a natural semi-graphic technique to include in statistical computing systems. This paper discusses the choices involved in implementing both automated and flexible versions of the display, develops an algorithm for the automated version, examines various implementation considerations, and presents a set of semi-portable...

This paper uses the concept of the triad census first introduced 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 ne...

Four commonly-used graph statistics, indices measured at the network level, are studied via Monte Carlo simulation. By implementing a simple trans- formation on these indices, we show that they are well approximated by the normal distribution. Consequently these approximations allow a researcher to use fun- damental significance testing to answer a...