@article{ribeiroQuantifyingEffectTemporal2013,
  langid = {english},
  title = {Quantifying the Effect of Temporal Resolution on Time-Varying Networks},
  volume = {3},
  issn = {2045-2322},
  url = {https://www.nature.com/articles/srep03006},
  doi = {10.1038/srep03006},
  abstract = {Time-varying networks describe a wide array of systems whose constituents and interactions evolve over time. They are defined by an ordered stream of interactions between nodes, yet they are often represented in terms of a sequence of static networks, each aggregating all edges and nodes present in a time interval of size Δt. In this work we quantify the impact of an arbitrary Δt on the description of a dynamical process taking place upon a time-varying network. We focus on the elementary random walk, and put forth a simple mathematical framework that well describes the behavior observed on real datasets. The analytical description of the bias introduced by time integrating techniques represents a step forward in the correct characterization of dynamical processes on time-varying graphs.},
  journaltitle = {Scientific Reports},
  urldate = {2018-08-22},
  date = {2013-10-21},
  pages = {3006},
  author = {Ribeiro, Bruno and Perra, Nicola and Baronchelli, Andrea},
  file = {/home/dimitri/Nextcloud/Zotero/storage/9WPT9TVJ/Ribeiro et al. - 2013 - Quantifying the effect of temporal resolution on t.pdf;/home/dimitri/Nextcloud/Zotero/storage/5IKE4WIN/srep03006.html}
}

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