article

Graph evolution: Densification and shrinking diameters

Authors:

Christos FaloutsosAuthors Info & Claims

ACM Transactions on Knowledge Discovery from Data (TKDD), Volume 1, Issue 1

Pages 2 - es

https://doi.org/10.1145/1217299.1217301

Published: 01 March 2007 Publication History

Abstract

How do real graphs evolve over time? What are normal growth patterns in social, technological, and information networks? Many studies have discovered patterns in static graphs, identifying properties in a single snapshot of a large network or in a very small number of snapshots; these include heavy tails for in- and out-degree distributions, communities, small-world phenomena, and others. However, given the lack of information about network evolution over long periods, it has been hard to convert these findings into statements about trends over time.

Here we study a wide range of real graphs, and we observe some surprising phenomena. First, most of these graphs densify over time with the number of edges growing superlinearly in the number of nodes. Second, the average distance between nodes often shrinks over time in contrast to the conventional wisdom that such distance parameters should increase slowly as a function of the number of nodes (like O(log n) or O(log(log n)).

Existing graph generation models do not exhibit these types of behavior even at a qualitative level. We provide a new graph generator, based on a forest fire spreading process that has a simple, intuitive justification, requires very few parameters (like the flammability of nodes), and produces graphs exhibiting the full range of properties observed both in prior work and in the present study.

We also notice that the forest fire model exhibits a sharp transition between sparse graphs and graphs that are densifying. Graphs with decreasing distance between the nodes are generated around this transition point.

Last, we analyze the connection between the temporal evolution of the degree distribution and densification of a graph. We find that the two are fundamentally related. We also observe that real networks exhibit this type of relation between densification and the degree distribution.

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Index Terms

Graph evolution: Densification and shrinking diameters
1. Information systems
  1. Information systems applications
    1. Data mining

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cover image ACM Transactions on Knowledge Discovery from Data

ACM Transactions on Knowledge Discovery from Data Volume 1, Issue 1

March 2007

161 pages

ISSN:1556-4681

EISSN:1556-472X

DOI:10.1145/1217299

Issue’s Table of Contents

Copyright © 2007 ACM.

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Published: 01 March 2007

Published in TKDD Volume 1, Issue 1

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