Evolution on a Dancing Landscape: Organizations and Networks in Dynamic Blau Space

McPherson, J. Miller; Ranger‐Moore, James

doi:10.2307/2580060

Cited by 151 publications

(108 citation statements)

References 18 publications

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“…In particular, the social network literature defines a concept of Blau-spaces [34,35] where socio-demographic attributes act as dimensions. Organizing force in Blau space is homophily as it has been argued that the flow of information between a pair of nodes decreases with the "distance" in the corresponding Blau space.…”

Section: The Multiplicative Attributes Graph (Mag) Modelmentioning

confidence: 99%

Multiplicative Attribute Graph Model of Real-World Networks

Kim

Leskovec

2010

Algorithms and Models for the Web-Graph

122

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Large scale real-world network data such as social and information networks are ubiquitous. The study of such social and information networks seeks to find patterns and explain their emergence through tractable models. In most networks, and especially in social networks, nodes have a rich set of attributes (e.g., age, gender) associated with them.Here we present a model that we refer to as the Multiplicative Attribute Graphs (MAG), which naturally captures the interactions between the network structure and the node attributes. We consider a model where each node has a vector of categorical latent attributes associated with it. The probability of an edge between a pair of nodes then depends on the product of individual attribute-attribute affinities. The model yields itself to mathematical analysis and we derive thresholds for the connectivity and the emergence of the giant connected component, and show that the model gives rise to networks with a constant diameter. We analyze the degree distribution to show that MAG model can produce networks with either log-normal or power-law degree distributions depending on certain conditions.

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Section: The Multiplicative Attributes Graph (Mag) Modelmentioning

confidence: 99%

Multiplicative Attribute Graph Model of Real-World Networks

Kim

Leskovec

2010

Algorithms and Models for the Web-Graph

122

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“…Moreover, people have to be in the neighbourhood at the same time. The greater the synchronization of people's time schedules, the better the community life is expected to be (Miller McPherson and Ranger-Moore, 1991;Blokland, 2003).…”

Section: Meeting Opportunitiesmentioning

confidence: 99%

When Are Neighbourhoods Communities? Community in Dutch Neighbourhoods

Völker¹,

Flap

Lindenberg

2006

European Sociological Review

188

153

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This study investigates the degree to which community can be found in Dutch neighbourhoods and attempts to explain why there is more community in some neighbourhoods than in others. We apply a perspective on community which assumes that people create communities with the expectation to realize some important well-being goals. Conditions that account for the creation of a local community are specified, i.e. the opportunity, ease, and motivation to do so. These conditions are realized when (i) neighbourhoods have more meeting places; (ii) neighbours are, given their resources and interests, motivated to invest in local relationships; (iii) neighbours have few relations outside of the neighbourhood, and (iv) neighbours are mutually interdependent. Data from the Survey of Social Networks of the Dutch on 1,007 respondents in 168 neighbourhoods are used. Results show that there is a sizeable amount of community in Dutch neighbourhoods and that all the four conditions contribute to the explanation, while interdependencies among neighbours have the strongest impact on the creation of community.

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“…There is a broad literature building on the work of Simmel (1955) and Blau (1977; suggesting that social distance along a number of dimensions can affect social interactions (McPherson and Ranger-Moore 1991). Given that a key insight of social disorganization theory is that neighborhoods with fewer social interactions will have more crime due to a reduced ability to provide informal social control, exploring any social dimensions that might affect social interaction is crucial.…”

mentioning

confidence: 99%

Micro-structure in micro-neighborhoods: A new social distance measure, and its effect on individual and aggregated perceptions of crime and disorder

Hipp

2010

Social Networks

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Evolution on a Dancing Landscape: Organizations and Networks in Dynamic Blau Space

Cited by 151 publications

References 18 publications

Multiplicative Attribute Graph Model of Real-World Networks

Multiplicative Attribute Graph Model of Real-World Networks

When Are Neighbourhoods Communities? Community in Dutch Neighbourhoods

Micro-structure in micro-neighborhoods: A new social distance measure, and its effect on individual and aggregated perceptions of crime and disorder

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