Social relationships differ in strength and in how they are maintained through online and offline interactions. This is manifested through the heterogeneity of tie strengths in egocentric networks that depict personal network structure. Egocentric networks are—at least in the empirical sense—inherently multilayered. While one can always imagine an underlying “true” network, observable social ties always reflect only a narrow cross-section, e.g., mobile phone calls, emails, or physical proximity recorded by sensors. I will talk about egocentric networks built from empirical data, discussing their salient features as well as similarities and differences across layers — e.g., between networks reconstructed from mobile phone calls or Bluetooth-based proximity. Finally, I will also discuss some recent modelling efforts that reproduce the observed tie strength heterogeneity in egocentric networks.
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Jari Saramäki is a full professor and vice head at the Department of Computer Science, Aalto University, Finland. He received his PhD in applied physics in 1998, studying quantum crystals at milliKelvin temperatures. After some career twists and turns involving what would nowadays be called data science, he returned to academia to study complex networks, a new and rapidly expanding field at that time. Since then, his broad range of research interests has included topics from ant supercolonies to the human immune system in addition to temporal networks of human interactions and social networks reconstructed from mobile telephone data.