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Power-Law Distributions in Empirical Data
TLDR
This work proposes a principled statistical framework for discerning and quantifying power-law behavior in empirical data by combining maximum-likelihood fitting methods with goodness-of-fit tests based on the Kolmogorov-Smirnov (KS) statistic and likelihood ratios. Expand
Finding community structure in very large networks.
TLDR
A hierarchical agglomeration algorithm for detecting community structure which is faster than many competing algorithms: its running time on a network with n vertices and m edges is O (md log n) where d is the depth of the dendrogram describing the community structure. Expand
Hierarchical structure and the prediction of missing links in networks
TLDR
This work presents a general technique for inferring hierarchical structure from network data and shows that the existence of hierarchy can simultaneously explain and quantitatively reproduce many commonly observed topological properties of networks. Expand
Finding local community structure in networks.
  • A. Clauset
  • Mathematics, Medicine
  • Physical review. E, Statistical, nonlinear, and…
  • 4 March 2005
TLDR
This work defines both a measure of local community structure and an algorithm that infers the hierarchy of communities that enclose a given vertex by exploring the graph one vertex at a time, and uses this algorithm to extract meaningful local clustering information in the large recommender network of an online retailer. Expand
Performance of modularity maximization in practical contexts.
TLDR
It is shown that the modularity function Q exhibits extreme degeneracies: it typically admits an exponential number of distinct high-scoring solutions and typically lacks a clear global maximum, implying that the output of any modularity maximization procedure should be interpreted cautiously in scientific contexts. Expand
Learning Latent Block Structure in Weighted Networks
TLDR
This model learns from both the presence and weight of edges, allowing it to discover structure that would otherwise be hidden when weights are discarded or thresholded, and a Bayesian variational algorithm is described for efficiently approximating this model's posterior distribution over latent block structures. Expand
A communal catalogue reveals Earth’s multiscale microbial diversity
TLDR
A meta-analysis of microbial community samples collected by hundreds of researchers for the Earth Microbiome Project is presented, creating both a reference database giving global context to DNA sequence data and a framework for incorporating data from future studies, fostering increasingly complete characterization of Earth’s microbial diversity. Expand
Systematic inequality and hierarchy in faculty hiring networks
TLDR
It is found that faculty hiring follows a common and steeply hierarchical structure that reflects profound social inequality and increased institutional prestige leads to increased faculty production, better faculty placement, and a more influential position within the discipline. Expand
Scale-free networks are rare
TLDR
A severe test of their empirical prevalence using state-of-the-art statistical tools applied to nearly 1000 social, biological, technological, transportation, and information networks finds robust evidence that strongly scale-free structure is empirically rare, while for most networks, log-normal distributions fit the data as well or better than power laws. Expand
On the Frequency of Severe Terrorist Events
In the spirit of Lewis Richardson’s original study of the statistics of deadly conflicts, we study the frequency and severity of terrorist attacks worldwide since 1968. We show that these events areExpand
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