Neighborhood-Based Models for Social Networks
Bibliographic Data
| ID | 6169764 |
|---|---|
| Authors | P Pattison (0000-0001-9626-2897, The University of Melbourne), G Robins (0000-0001-7538-5804, The University of Melbourne) |
| Year | 2002 |
| Volume | 32 |
| Issue | 1 |
| Pages | 301-337 |
| Publication date | 2002-08-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Sociological Methodology (JOURNAL) |
| Journal identifiers | ISSN: 0081-1750 • E-ISSN: 1467-9531 |
| Publisher | SAGE Publishing (PUBLISHER • US) |
| DOI | 10.1111/1467-9531.00119 |
| OpenAlex | W2057583855 |
| Language | EN |
| Citations received | 96 |
| References cited | 46 |
We argue that social networks can be modeled as the outcome of processes that occur in overlapping local regions of the network, termed local social neighborhoods. Each neighborhood is conceived as a possible site of interaction and corresponds to a subset of possible network ties. In this paper, we discuss hypotheses about the form of these neighborhoods, and we present two new and theoretically plausible ways in which neighborhood-based models for networks can be constructed. In the first, we introduce the notion of a setting structure, a directly hypothesized (or observed) set of exogenous constraints on possible neighborhood forms. In the second, we propose higher-order neighborhoods that are generated, in part, by the outcome of interactive network processes themselves. Applications of both approaches to model construction are presented, and the developments are considered within a general conceptual framework of locale for social networks. We show how assumptions about neighborhoods can be cast within a hierarchy of increasingly complex models; these models represent a progressively greater capacity for network processes to “reach” across a network through long cycles or semipaths. We argue that this class of models holds new promise for the development of empirically plausible models for networks and network-based processes
Class (philosophy · Complex network · Dynamic network analysis · Economics · Evolving networks · Hierarchy · Mathematical economics · Network formation · Network model · Network science · Network structure · Outcome (game theory · Set (abstract data type · Social network (sociolinguistics · Social network analysis · Artificial Intelligence · Complex Network Analysis Techniques · Computer Science · Mathematics · Opinion Dynamics and Social Influence · Social Capital and Networks · Theoretical Computer Science
Ergm
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| Unique citing works | 96 |
|---|---|
| Citations per year | 3,84 |
| Citation span | 2001 - 2025 (25) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 96 |