Work

Community detection in sparse latent space models

Year: 2020

Type: preprint

Abstract: We show that a simple community detection algorithm originated from stochastic blockmodel literature achieves consistency, and even optimality, for a broad and flexible class of sparse latent space models. The class of models includes latent eigenmodels (arXiv:0711.1146). The community detection algorithm is based on spectral clustering followed by local refinement via normalized edge counting.

Source: arXiv (Cornell University)

DOI: 10.48550/arxiv.2008.01375

Authors: Gao, Fengnan, Ma, Zongming, Yuan, Hongsong

Institutions: Fudan University, University of Pennsylvania, Shanghai University of Finance and Economics

Language: English

Topic: Complex Network Analysis Techniques

Subfield: Statistical and Nonlinear Physics

Field: Physics and Astronomy

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W3047620458

Cites: 21

Cited by: 3

Related to: 10