Sampling bias in systems with structural heterogeneity and limited internal diffusion

J. P. Onnela, N. F. Johnson, S. Gourley, G. Reinert, M. Spagat

Research output: Contribution to journalArticle

1 Scopus citations

Abstract

Complex-systems research is becomingly increasingly data-driven, particularly in the social and biological domains. Many of the systems from which sample data are collected feature structural heterogeneity at the mesoscopic scale (i.e. communities) and limited inter-community diffusion. Here we show that the interplay between these two features can yield a significant bias in the global characteristics inferred from the data. We present a general framework to quantify this bias, and derive an explicit corrective factor for a wide class of systems. Applying our analysis to a recent high-profile survey of conflict mortality in Iraq suggests a significant overestimate of deaths.

Original languageEnglish (US)
Article number28001
JournalEPL
Volume85
Issue number2
DOIs
StatePublished - Aug 25 2009

ASJC Scopus subject areas

  • Physics and Astronomy(all)

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    Onnela, J. P., Johnson, N. F., Gourley, S., Reinert, G., & Spagat, M. (2009). Sampling bias in systems with structural heterogeneity and limited internal diffusion. EPL, 85(2), [28001]. https://doi.org/10.1209/0295-5075/85/28001