1 code implementation • 15 Mar 2014 • Lucas G. S. Jeub, Prakash Balachandran, Mason A. Porter, Peter J. Mucha, Michael W. Mahoney
In this paper, we adopt a complementary perspective that "communities" are associated with bottlenecks of locally-biased dynamical processes that begin at seed sets of nodes, and we employ several different community-identification procedures (using diffusion-based and geodesic-based dynamics) to investigate community quality as a function of community size.
Social and Information Networks Disordered Systems and Neural Networks Combinatorics Adaptation and Self-Organizing Systems Physics and Society
no code implementations • 18 Oct 2015 • Lucas G. S. Jeub, Michael W. Mahoney, Peter J. Mucha, Mason A. Porter
The analysis of multilayer networks is among the most active areas of network science, and there are now several methods to detect dense "communities" of nodes in multilayer networks.
Social and Information Networks Probability Adaptation and Self-Organizing Systems Data Analysis, Statistics and Probability Physics and Society
no code implementations • 23 Feb 2021 • Guilherme Ferraz de Arruda, Lucas G. S. Jeub, Angélica S. Mata, Francisco A. Rodrigues, Yamir Moreno
Rumor and information spreading are natural processes that emerge from human-to-human interaction.
Physics and Society
2 code implementations • 26 Jul 2021 • Lucas G. S. Jeub, Giovanni Colavizza, Xiaowen Dong, Marya Bazzi, Mihai Cucuringu
Our local2global approach proceeds by first dividing the input graph into overlapping subgraphs (or "patches") and training local representations for each patch independently.
no code implementations • 12 Jan 2022 • Lucas G. S. Jeub, Giovanni Colavizza, Xiaowen Dong, Marya Bazzi, Mihai Cucuringu
Our local2global approach proceeds by first dividing the input graph into overlapping subgraphs (or "patches") and training local representations for each patch independently.