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 language | English (US) |
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Article number | 28001 |
Journal | EPL |
Volume | 85 |
Issue number | 2 |
DOIs | |
State | Published - 2009 |
ASJC Scopus subject areas
- Physics and Astronomy(all)