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Publication Detail
The role of space, time and sociability in predicting social encounters
  • Publication Type:
    Journal article
  • Authors:
    Stich C, Tranos E, Musolesi M, Lehmann S
  • Publication date:
    04/06/2021
  • Journal:
    Environment and Planning B: Urban Analytics and City Science
  • Status:
    Accepted
  • Language:
    English
  • Keywords:
    Geographic context, link prediction, social networks
  • Notes:
    © 2021 by SAGE Publications. This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/).
Abstract
Space, time and the social realm are intrinsically linked. While an array of studies have tried to untangle these factors and their influence on human behaviour, hardly any have taken their effects into account at the same time. To disentangle these factors, we try to predict future encounters between students and assess how important social, spatial and temporal features are for prediction. We phrase our problem of predicting future encounters as a link-prediction problem and utilise set of Random Forest predictors for the prediction task. We use data collected by the Copenhagen network study; a study unique in scope and scale and tracks 847 students via mobile phones over the course of a whole academic year. We find that network and social features hold the highest discriminatory power for predicting future encounters.
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