Testing the hypothesis of preferential attachment in social network formation

House, Thomas and Read, Jonathan M. and Danon, Leon and Keeling, Matthew J. (2015) Testing the hypothesis of preferential attachment in social network formation. EPJ Data Science, 4 (1). ISSN 2193-1127

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Abstract

The hypothesis of preferential attachment (PA) - whereby better connected individuals make more connections - is hotly debated, particularly in the context of epidemiological networks. The simplest models of PA, for example, are incompatible with the eradication of any disease through population-level control measures such as random vaccination. Typically, evidence has been sought for the presence or absence of preferential attachment via asymptotic power-law behaviour. Here, we present a general statistical method to test directly for evidence of PA in count data and apply this to data for contacts relevant to the spread of respiratory diseases. We find that while standard methods for model selection prefer a form of PA, careful analysis of the best fitting PA models allows for a level of contact heterogeneity that in fact allows control of respiratory diseases. Our approach is based on a flexible but numerically cheap likelihood-based model that could in principle be applied to other integer data where the hypothesis of PA is of interest.

Item Type:
Journal Article
Journal or Publication Title:
EPJ Data Science
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/1700/1706
Subjects:
ID Code:
84458
Deposited By:
Deposited On:
30 Jan 2017 16:04
Refereed?:
Yes
Published?:
Published
Last Modified:
04 Jun 2020 03:06