Testing the hypothesis of preferential attachment in social network formation

Thomas House, Jonathan M Read, Leon Danon, Matthew J Keeling

    Research output: Contribution to journalArticlepeer-review

    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.
    Original languageEnglish
    JournalEPJ Data Science
    Volume4
    Issue number13
    DOIs
    Publication statusPublished - 2015

    Keywords

    • MLE; Phase-type distribution; model selection; spectral methods

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