Statistical Analysis of Network Data

By Eric D. Kolaczyk. 2009

968 citations recorded by the source corpus.

Subfields: Geometry and Topology, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/3dc3e9fcc521c9e1a4f35ed9e215919b7ed957d2

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In Geometry and Topology

In Statistical and Nonlinear Physics

Citations in the corpus

Network analysis: an integrative approach to the structure of psychopathology. (2013, background): “A good introductory text on the resulting literature is Newman (2010), while Kolaczyk (2009) and Barrat and associates (2008) yield excellent treatments of the applications of network modeling in dynamic models.”
State of the aRt personality research: A tutorial on network analysis of personality data in R (2015, positive): “Not all nodes in a network are equally important in determining the network’s structure and, if processes run on the network, in determining its dynamic characteristics (Kolaczyk, 2009).”
Network Topology Inference from Spectral Templates (2016, methodology): “ceptualized as signals defined on the vertices of a graph [3], [4].”
Statistical Inference on Random Dot Product Graphs: a Survey (2017, background): “Statistical inference on random graphs and networks, in particular, has witnessed extraordinary growth over the last decade: for example, [41, 51] discuss the considerable applications in recent network science of several canonical random graph models.”
Estimating psychological networks and their accuracy: A tutorial paper (2016, methodology): “…of probabilistic network models (e.g., Epskamp et al. 2016; Koller and Friedman 2009; Lauritzen 1996), as well as network inference techniques, such as centrality measures, that can be used once a network is obtained (e.g., Costantini et al. 2015a; Kolaczyk 2009; Newman 2004; Sporns et al. 2004).”
How Does the Data Sampling Strategy Impact the Discovery of Information Diffusion in Social Media? (2010, methodology): “Moreover, the non-uniformities within each sampling process also have not been considered, nor have we evaluated the bias in each strategy using any form of sampling bias estimators (Kolaczyk 2009).”
Random graphs with a given degree sequence (2010, background): “By Sourav Chatterjee1, Persi Diaconis and Allan Sly”
The social distributional hypothesis: a pragmatic proxy for homophily in online social networks (2014, positive): “Many observations of network properties can be explained just by the network's degree distribution (Kolaczyk 2009).”