JOURNAL ARTICLE

Estimating node similarity from co-citation in a spatial graph model

Abstract

Co-citation (number of nodes linking to both of a given pair of nodes) is often used heuristically to judge similarity between nodes in a complex network. We investigate the relation between node similarity and co-citation in the context of the Spatial Preferred Attachment (SPA) model. The SPA model is a spatial model, where nodes live in a metric space, and nodes that are close together in space are considered similar, and are more likely to link to one another.

Keywords:
Similarity (geometry) Node (physics) Computer science Context (archaeology) Relation (database) Graph Metric (unit) Theoretical computer science Citation Link (geometry) Metric space Data mining Topology (electrical circuits) Mathematics Artificial intelligence Combinatorics Discrete mathematics Computer network Geography World Wide Web Engineering

Metrics

10
Cited By
1.66
FWCI (Field Weighted Citation Impact)
14
Refs
0.84
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Complex Network Analysis Techniques
Physical Sciences →  Physics and Astronomy →  Statistical and Nonlinear Physics
Spatial and Panel Data Analysis
Social Sciences →  Economics, Econometrics and Finance →  Economics and Econometrics
Geographic Information Systems Studies
Social Sciences →  Social Sciences →  Geography, Planning and Development

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