9. Neighborhood-Based Models for Social Networks

By P. Pattison, Garry Robins. 2002

310 citations recorded by the source corpus.

Subfields: Sociology and Political Science, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/a4ec0c0867a610979fc8bea67f575b9363e0c749

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Citations in the corpus

Networks beyond pairwise interactions: structure and dynamics (2020, background): “[220] Philippa Pattison and Garry Robins.”
ergm: A Package to Fit, Simulate and Diagnose Exponential-Family Models for Networks. (2008, background): “These models relax the one-step Markovian dependence assumptions, allowing investigation of longer range congurations, such as longer paths in the network or larger cycles ( Pattison and Robins 2002 ).”
Advances in exponential random graph (p*) models applied to a large social network (2007, background): “1 For a more in-depth discussion of this concept see Pattison and Robins (2002).”
Recent developments in exponential random graph (p*) models for social networks (2007, methodology): “The alternating k-triangle assumption moves beyond the dependence assumptions underlying Markov random graph models, utilizing instead the partial dependence concept proposed by Pattison and Robins (2002).”
An introduction to exponential random graph (p*) models for social networks (2007, methodology): “A second direction presented by Pattison and Robins (2002) was to propose non-Markov dependencies among ties that did not share an actor but might be interdependent through third party links.”
Understanding network formation in strategy research: Exponential random graph models (2016, background): “To implement ERGMs, it is important to understand the dependence assumptions that define the ways in which the observed ties may be related (Brandes et al., 2013; Pattison and Robins, 2002; Robins et al., 2007a).”
Social Network Analysis with sna (2008, unknown): “This theory has been considerably enriched in recent decades (see, e.g., Frank and Strauss 1986; Pattison and Robins 2002), particularly with respect to the connection between edgewise dependence conditions and structural biases (see Wasserman and Robins (2005) for an approachable introduction).”
Testing Multitheoretical, Multilevel Hypotheses About Organizational Networks: An Analytic Framework and Empirical Example (2006, methodology): “This logic is central to random graph models and to statistical models including Markov random graph models (Frank & Strauss, 1986; Strauss & Ikeda, 1990) and the p* family of models (Anderson, Wasserman, & Crouch, 1999; Pattison & Robins, 2002; Pattison & Wasserman, 1999; Robins, Elliott, & Patti”
Exponential random graph models for multilevel networks (2013, methodology): “…1986) where a pair of tie variables are considered conditionally independent unless they have a node in common; and the social circuit assumptions (Pattison and Robins, 2002, 2004; Snijders et al., 2006) where tie variables within a social circuit (four-cycle) are considered conditionally…”
DYNAMIC NETWORKS AND BEHAVIOR: SEPARATING SELECTION FROM INFLUENCE: separating selection from influence (2010, background): “The argument can be extended to also cover informal forms of social settings, such as the opportunity structure of meeting others that is implied by the social network itself (PATTISON & ROBINS 2002).”
Closure, connectivity and degree distributions: Exponential random graph (p*) models for directed social networks (2009, background): “Specifically, ollowing the partial dependence approach of Pattison and Robins 2002), Snijders et al. assumed that two possible edges are condiionally dependent when, if they were observed, they would form a our-cycle in the network.”
4. A Relational Event Framework for Social Action (2008, background): “…burgeoning literature on choice of sufficient statistics (e.g., Wasserman and Pattison [1996]; Pattison and Wasserman [1999]; Robins et al. [1999]; Pattison and Robins [2002]; Handcock [2003]; Snijders et al. [2006]; Butts [2006]), a broad implication of which is the importance of selecting…”
Social network analysis: A methodological introduction (2008, methodology): “…of GLI scores associated with a given network, it is thus possible in some cases to infer properties of the social process which gave rise to it; examination of such process/feature connections is an area of active theoretical research (Pattison & Robins, 2002; Robins, Pattison, & Woolcock, 2005).”
Small Worlds Among Interlocking Directors: Network Structure and Distance in Bipartite Graphs (2004, background): “Additionally, social neighbourhood processes may be structured and constrained by their social setting structure (Pattison and Robins, 2002; see also Feld, 1981; Mische and White, 1998; Mische and Robins, 2002; White, 1995).”