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13
Representing Degree Distributions, Clustering, and Homophily in Social Networks With Latent Cluster Random Effects Models
, 2007
"... preparation of this paper. Social network data often involve transitivity, homophily on observed attributes, clustering, and heterogeneity of actors. We propose the latent cluster random effects model to take account of all of these features, and we describe a Bayesian estimation method. The model f ..."
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Cited by 6 (1 self)
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preparation of this paper. Social network data often involve transitivity, homophily on observed attributes, clustering, and heterogeneity of actors. We propose the latent cluster random effects model to take account of all of these features, and we describe a Bayesian estimation method. The model fits two real datasets well. We show by simulation that networks with the same degree distribution can have very different clustering behaviors. This suggests that scalefree and smallworld network models may not be adequate for all types of network, while our model recovers both the clustering and the degree distribution. 1
StOCNET: software for the statistical analysis of social networks
 Connections
, 2003
"... This paper gives a stateoftheart overview of available software for the statistical analysis of social networks as of Summer 2004. It reviews and compares software packages for social network analysis with respect to their statistical procedures, illustrating some procedures with example data. Th ..."
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Cited by 5 (1 self)
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This paper gives a stateoftheart overview of available software for the statistical analysis of social networks as of Summer 2004. It reviews and compares software packages for social network analysis with respect to their statistical procedures, illustrating some procedures with example data. The choice of routines that were inspected is restricted to procedures for statistical modeling based on probability distributions (e.g., exponential random graph models, QAP correlation, statistical analysis of longitudinal network data). This definition of analysis routines excludes the extensive review of procedurebased routines based on more complex (iterative) algorithms like cluster analysis or eigendecompositions. The paper concludes with some recommendations. Key words: exponential random graph model, longitudinal network data, statistical modelling, software packages, permutation tests. 1
The Network Structure of Informal Arrangements: Evidence from Rural Tanzania
, 2007
"... In developing countries, whenever formal economic and financial institutions lack strength, households are forced to rely on risk sharing and other informal arrangements based on preexisting interpersonal relationships. This paper takes a network perspective to investigate how rural households form ..."
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In developing countries, whenever formal economic and financial institutions lack strength, households are forced to rely on risk sharing and other informal arrangements based on preexisting interpersonal relationships. This paper takes a network perspective to investigate how rural households form the links through which they provide and/or get economic support, and whether the connection structure of the community affects the formation of these links. I test the hypothesis that indirect contacts matter, that is, agents take into account not only potential partners’ characteristics, but also their position with respect to all other agents. A network formation framework with fully heterogeneous agents is first presented, following Jackson and Wolinsky (1996), an estimation procedure is then proposed and applied to data on a village in rural Tanzania. Results show that when agents evaluate the net advantage of forming a link they also consider the relative position and the wealth of indirect partners. My paper contributes to both network theory and the literature on risk sharing arrangements in that it proposes an innovative procedure to estimate endogenous network formation models, and provides evidence that network structure has an explanatory value disregarded by all previous studies, which are focused on direct relations only.
Likelihoods for fixed rank nomination networks
, 2012
"... Many studies that gather social network data use survey methods that lead to censored, missing or otherwise incomplete information. For example, the popular fixed rank nomination (FRN) scheme, often used in studies of schools and businesses, asks study participants to nominate and rank at most a sma ..."
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Cited by 1 (1 self)
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Many studies that gather social network data use survey methods that lead to censored, missing or otherwise incomplete information. For example, the popular fixed rank nomination (FRN) scheme, often used in studies of schools and businesses, asks study participants to nominate and rank at most a small number of contacts or friends, leaving the existence other relations uncertain. However, most statistical models are formulated in terms of completely observed binary networks. Statistical analyses of FRN data with such models ignore the censored and ranked nature of the data and could potentially result in misleading statistical inference. To investigate this possibility, we compare parameter estimates obtained from a likelihood for complete binary networks to those from a likelihood that is derived from the FRN scheme, and therefore recognizes the ranked and censored nature of the data. We show analytically and via simulation that the binary likelihood can provide misleading inference, at least for certain model parameters that relate network ties to characteristics of individuals and pairs of individuals. We also compare these different likelihoods in a data analysis of several adolescent social networks. For some of these networks, the parameter estimates from the binary and FRN likelihoods lead to different conclusions, indicating the importance of analyzing FRN data with a method that accounts for the FRN survey design.
INSNA Conference Papers
"... Title: Social network analysis in analyzing potential collaborators Since the tragic events of the September 11, 2001 attacks in the United States, social network analysis has increasingly been used to study terrorist networks. Terrorism, together with such crimes as drug trafficking, armed robberie ..."
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Title: Social network analysis in analyzing potential collaborators Since the tragic events of the September 11, 2001 attacks in the United States, social network analysis has increasingly been used to study terrorist networks. Terrorism, together with such crimes as drug trafficking, armed robberies and fraud is called organized crime. Crime or criminal activities usually work in group which needs more than two people to communicate and to perform their secret plan. Traditionally, crime investigators or intelligent officer used investigation tools that are widely available in the market to provide graphical representation of the data network in order to facilitate and speed up their investigation. This paper proposes the combination of social network analysis strength which focuses on egocentric network method and important criteria for potential collaborators in identifying potential collaborators in telecommunication data set. Effectively combining multiple sources of data can lead intelligent officer to discover patterns in order to help them be more
Computational Mathematical Organization Theory 5:2 (1999): 167192
"... We propose a class of actororiented statistical models for closed social networks in general, and friendship networks in particular. The models are random utility models developed within a rational choice framework. Based on social psychological and sociological theories about friendship, mathemati ..."
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We propose a class of actororiented statistical models for closed social networks in general, and friendship networks in particular. The models are random utility models developed within a rational choice framework. Based on social psychological and sociological theories about friendship, mathematical functions capturing expected utility of individual actors with respect to friendship are constructed. Expected utility also contains a random (unexplained) component. We assume that, given their restrictions and contact opportunities, individuals evaluate their utility functions and behave such that they maximize the expected amount of utility. The behavior under consideration is the expression of like and dislike (choice of friends). Theoretical mechanisms that are modelled are, e.g., the principle of diminishing returns, the tendency towards reciprocated choices, and the preference for friendship relations with similar others. Constraints imposed on individuals are, e.g., the structure of the existing network, and the distribution of personal characteristics over the respondents. The models are illustrated by means of a dataset collected among university freshmen at 7 points in time during 1994 and 1995.
Statistical Methods for Network Dynamics (⋆) Metodi Statistici Per L’Analisi Dinamica Delle Reti
"... stima per l’analisi longitudinale di reti sociali. Per rappresentare i processi sottostanti le dinamiche di rete, è utile pensare ai dati di panel come ad osservazioni provenienti da un processo a tempo continuo definito sullo spazio dei grafi orientati. Vengono discussi e illustrati modelli stocast ..."
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stima per l’analisi longitudinale di reti sociali. Per rappresentare i processi sottostanti le dinamiche di rete, è utile pensare ai dati di panel come ad osservazioni provenienti da un processo a tempo continuo definito sullo spazio dei grafi orientati. Vengono discussi e illustrati modelli stocastici tieoriented e actororiented in grado di riflettere sia dinamiche endogene che effetti di variabili esogene. Tali modelli non consentono il calcolo esplicito ma possono essere sviluppati specifici schemi di simulazione. Sono inoltre proposti metodi di approssimazione stocastica per la stima dei parametri. Un esempio di applicazione di questi modelli è condotto sui dati reticolari provenienti da uno studio sul precursore della comunicazione via email.
Contents lists available at ScienceDirect Social Networks
"... journal homepage: www.elsevier.com/locate/socnet Representing degree distributions, clustering, and homophily in social networks ..."
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journal homepage: www.elsevier.com/locate/socnet Representing degree distributions, clustering, and homophily in social networks