no code implementations • 25 Nov 2020 • Homa Hosseinmardi, Amir Ghasemian, Aaron Clauset, Markus Mobius, David M. Rothschild, Duncan J. Watts
Although it is under-studied relative to other social media platforms, YouTube is arguably the largest and most engaging online media consumption platform in the world.
2 code implementations • 17 Sep 2019 • Amir Ghasemian, Homa Hosseinmardi, Aram Galstyan, Edoardo M. Airoldi, Aaron Clauset
These results indicate that the state-of-the-art for link prediction comes from combining individual algorithms, which achieves nearly optimal predictions.
1 code implementation • 21 Oct 2018 • Nora Connor, Aaron Clauset
Using a large, longitudinal data set of state level policies and their traits, we train models to predict (i) whether policies become national policy, and (ii) how many states must pass a given policy before it becomes national.
Computers and Society Physics and Society
no code implementations • 19 Jun 2018 • Juan Ignacio Perotti, Claudio Juan Tessone, Aaron Clauset, Guido Caldarelli
Modern statistical modeling is an important complement to the more traditional approach of physics where Complex Systems are studied by means of extremely simple idealized models.
Physics and Society Disordered Systems and Neural Networks Social and Information Networks Data Analysis, Statistics and Probability
1 code implementation • 28 Feb 2018 • Amir Ghasemian, Homa Hosseinmardi, Aaron Clauset
These results introduce both a theoretically principled approach to evaluate over and underfitting in models of network community structure and a realistic benchmark by which new methods may be evaluated and compared.
no code implementations • 31 Oct 2017 • Kansuke Ikehara, Aaron Clauset
A number of studies in the field have been focused on finding the common properties among different kinds of networks such as heavy-tail degree distribution, small-worldness and modular structure and they have tried to establish a theory of structural universality in complex networks.
no code implementations • 20 Aug 2016 • Leto Peel, Daniel B. Larremore, Aaron Clauset
We illustrate this point by introducing two statistical techniques that can quantify the relationship between metadata and community structure for a broad class of models.
no code implementations • 14 Jul 2015 • M. E. J. Newman, Aaron Clauset
For many networks of scientific interest we know both the connections of the network and information about the network nodes, such as the age or gender of individuals in a social network, geographic location of nodes in the Internet, or cellular function of nodes in a gene regulatory network.
no code implementations • 19 Jun 2015 • Amir Ghasemian, Pan Zhang, Aaron Clauset, Cristopher Moore, Leto Peel
We study the fundamental limits on learning latent community structure in dynamic networks.
no code implementations • 14 Nov 2014 • Abigail Z. Jacobs, Aaron Clauset
Here, we describe a unified view of generative models for networks that draws together many of these disparate threads and highlights the fundamental similarities and differences that span these fields.
no code implementations • 2 Apr 2014 • Christopher Aicher, Abigail Z. Jacobs, Aaron Clauset
We then evaluate the WSBM's performance on both edge-existence and edge-weight prediction tasks for a set of real-world weighted networks.
1 code implementation • 12 Mar 2014 • Daniel B. Larremore, Aaron Clauset, Abigail Z. Jacobs
Bipartite networks are a common type of network data in which there are two types of vertices, and only vertices of different types can be connected.
no code implementations • 5 Mar 2014 • Leto Peel, Aaron Clauset
Interactions among people or objects are often dynamic in nature and can be represented as a sequence of networks, each providing a snapshot of the interactions over a brief period of time.
no code implementations • 24 May 2013 • Christopher Aicher, Abigail Z. Jacobs, Aaron Clauset
We generalize the stochastic block model to the important case in which edges are annotated with weights drawn from an exponential family distribution.
no code implementations • 1 Sep 2012 • Aaron Clauset, Ryan Woodard
Quantities with right-skewed distributions are ubiquitous in complex social systems, including political conflict, economics and social networks, and these systems sometimes produce extremely large events.
7 code implementations • 7 Jun 2007 • Aaron Clauset, Cosma Rohilla Shalizi, M. E. J. Newman
Power-law distributions occur in many situations of scientific interest and have significant consequences for our understanding of natural and man-made phenomena.
Data Analysis, Statistics and Probability Disordered Systems and Neural Networks Applications Methodology
no code implementations • 9 Aug 2004 • Aaron Clauset, M. E. J. Newman, Cristopher Moore
Here we present 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(m d log n) where d is the depth of the dendrogram describing the community structure.
Statistical Mechanics Disordered Systems and Neural Networks