Extrapolative simulation of neighborhood networks based on population spatial distribution: Do they predict crime?

Hipp, John R.; Butts, Carter T.; Acton, Ryan M.; Nagle, Nicholas N.; Boessen, Adam

doi:10.1016/j.socnet.2013.07.002

Cited by 33 publications

(27 citation statements)

References 58 publications

(72 reference statements)

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“…In one of the few efforts to map entire social networks at the community level, Entwisle et al (2007) demonstrate that network structures vary meaningfully across villages in Thailand and partially explain village-level variability in the ability to locate and interview former residents. Hipp and colleagues (2013) simulate network ties within neighborhoods using a spatial interaction function (Butts et al 2012). Generating measures of neighborhood social network structure from simulated data, Hipp et al find evidence of network structure effects on crime rates in five cities.…”

Section: The Structure Of Shared Routines As An Ecological Networkmentioning

confidence: 99%

Ecological Networks and Neighborhood Social Organization

Browning

Calder

Soller³

et al. 2017

American Journal of Sociology

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Drawing on the social disorganization tradition and the social ecological perspective of Jane Jacobs, the authors hypothesize that neighborhoods composed of residents who intersect in space more frequently as a result of routine activities will exhibit higher levels of collective efficacy, intergenerational closure, and social network interaction and exchange. They develop this approach employing the concept of ecological networks—two-mode networks that indirectly link residents through spatial overlap in routine activities. Using data from the Los Angeles Family and Neighborhood Survey, they find evidence that econetwork extensity (the average proportion of households in the neighborhood to which a given household is tied through any location) and intensity (the degree to which household dyads are characterized by ties through multiple locations) are positively related to changes in social organization between 2000–2001 and 2006–2008. These findings demonstrate the relevance of econetwork characteristics—heretofore neglected in research on urban neighborhoods—for consequential dimensions of neighborhood social organization.

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Section: The Structure Of Shared Routines As An Ecological Networkmentioning

confidence: 99%

Ecological Networks and Neighborhood Social Organization

Browning

Calder

Soller³

et al. 2017

American Journal of Sociology

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“…These effects are sometimes applied as specific measures in research (e.g. Hipp et al 2013), but may have less clear behaviors when included with other network terms.…”

Section: Discussionmentioning

confidence: 99%

Diagnosing Multicollinearity in Exponential Random Graph Models

Duxbury¹

2017

Preprint

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Exponential random graph models (ERGM) have been widely applied in the social sciences in the past ten years. However, diagnostics for ERGM have lagged behind their use.Collinearity-type problems can emerge without detection when fitting ERGM, yielding inconsistent model estimates and problematizing inference from parameters. This article provides a method to detect multicollinearity in ERGM. It outlines the problem and provides a method to calculate the variance inflation factor from ERGM parameters. It then evaluates the method with a Monte Carlo simulation, fitting 216,000 ERGMs and calculating the variance inflation factors for each model. The distribution of variance inflation factors is analyzed using multilevel regression to determine what network characteristics lend themselves to collinearitytype problems. The relationship between variance inflation factors and unstable standard errors (a standard sign of collinearity) is also examined. The method is shown to effectively detect multicollinearity and guidelines for interpretation are discussed.

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“…Thus, we distinguished this section to include socio-economical relationships of the criminal and terrorist activities. We provided summaries and brief insights with respect to; (i) crime rates affected by ties among the neighborhoods and the crime and disorder distribution of the individuals along with their mobility between the neighborhoods Hipp et al (2013); Hipp (2010), (ii) investigation on loss of capital with the influence of social networks Baker & Faulkner (2004).…”

Section: Influence Of Socio-economic Relationships On Crime and Terrormentioning

confidence: 99%

“…Hipp et al (2013) propose to simulate network ties speculatively and construct structural network in lack of links between pairs in a social environment. They spatially locate the households in a city.…”

Section: Influence Of Socio-economic Relationships On Crime and Terrormentioning

confidence: 99%

A Survey of Social Network Forensics

Karabiyik¹,

Canbaz²,

Aksoy³

et al. 2016

JDFSL

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Social networks in any form, specifically online social networks (OSNs), are becoming a part of our everyday life in this new millennium especially with the advanced and simple communication technologies through easily accessible devices such as smartphones and tablets. The data generated through the use of these technologies need to be analyzed for forensic purposes when criminal and terrorist activities are involved. In order to deal with the forensic implications of social networks, current research on both digital forensics and social networks need to be incorporated and understood. This will help digital forensics investigators to predict, detect and even prevent any criminal activities in different forms. It will also help researchers to develop new models/techniques in the future. This paper provides literature review of the social network forensics methods, models, and techniques in order to provide an overview to the researchers for their future works as well as the law enforcement investigators for their investigations when crimes are committed in the cyber space. It also provides awareness and defense methods for OSN users in order to protect them against to social attacks.

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Extrapolative simulation of neighborhood networks based on population spatial distribution: Do they predict crime?

Cited by 33 publications

References 58 publications

Ecological Networks and Neighborhood Social Organization

Ecological Networks and Neighborhood Social Organization

Diagnosing Multicollinearity in Exponential Random Graph Models

A Survey of Social Network Forensics

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