Add to ORKGThis techniques guide provides a brief answer to the question: How to choose a dichotomization threshold? We propose a two step approach to selecting a dichotomization threshold. We illustrate the approaches using two datasets and provide instructions on how to perform these approaches in R and UCINET
Structural brain networks derived from diffusion magnetic resonance imaging data have been used exte...
Journal of Defense Modeling and Simulation 12(2):157-65In a social network analysis the output provi...
A general approach to exploratory analysis and modeling of network data is to investigate dyad distr...
In order to conduct analyses of networked systems where connections between individuals take on a ra...
<p>Two broad classes of networks naturally occur in real world settings based on whether interaction...
The authors examine the practice of dichotomization of quantitative measures, wherein relationships ...
We present an algorithm for decomposing a social network into an optimal number of structurally equi...
Real-world data can often be represented as a heterogeneous network relating nodes of different type...
Multilayer networks arise when there exists more than one source of relationship for a ...
Despite the increasingly broad perceptual capabilities of neural networks, applying them to new task...
This dissertation consists of two parts. In the first part, a learning-based method for classificati...
This paper introduces and tests a novel methodology for measuring networks. Rather than collecting d...
A long-standing open problem with direct blockmodeling is that it is explicitly intended for binary,...
A common characteristic of relational data sets ---degree disparity---can lead relational learning ...
<p>(A) WNFN in the L-choice task (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.p...
Structural brain networks derived from diffusion magnetic resonance imaging data have been used exte...
Journal of Defense Modeling and Simulation 12(2):157-65In a social network analysis the output provi...
A general approach to exploratory analysis and modeling of network data is to investigate dyad distr...
In order to conduct analyses of networked systems where connections between individuals take on a ra...
<p>Two broad classes of networks naturally occur in real world settings based on whether interaction...
The authors examine the practice of dichotomization of quantitative measures, wherein relationships ...
We present an algorithm for decomposing a social network into an optimal number of structurally equi...
Real-world data can often be represented as a heterogeneous network relating nodes of different type...
Multilayer networks arise when there exists more than one source of relationship for a ...
Despite the increasingly broad perceptual capabilities of neural networks, applying them to new task...
This dissertation consists of two parts. In the first part, a learning-based method for classificati...
This paper introduces and tests a novel methodology for measuring networks. Rather than collecting d...
A long-standing open problem with direct blockmodeling is that it is explicitly intended for binary,...
A common characteristic of relational data sets ---degree disparity---can lead relational learning ...
<p>(A) WNFN in the L-choice task (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.p...
Structural brain networks derived from diffusion magnetic resonance imaging data have been used exte...
Journal of Defense Modeling and Simulation 12(2):157-65In a social network analysis the output provi...
A general approach to exploratory analysis and modeling of network data is to investigate dyad distr...