Universal patterns in egocentric communication networks
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A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
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en
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9
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Nature Communications, Volume 14, issue 1, pp. 1-9
Abstract
Tie strengths in social networks are heterogeneous, with strong and weak ties playing different roles at the network and individual levels. Egocentric networks, networks of relationships around an individual, exhibit few strong ties and more weaker ties, as evidenced by electronic communication records. Mobile phone data has also revealed persistent individual differences within this pattern. However, the generality and driving mechanisms of social tie strength heterogeneity remain unclear. Here, we study tie strengths in egocentric networks across multiple datasets of interactions between millions of people during months to years. We find universality in tie strength distributions and their individual-level variation across communication modes, even in channels not reflecting offline social relationships. Via a simple model of egocentric network evolution, we show that the observed universality arises from the competition between cumulative advantage and random choice, two tie reinforcement mechanisms whose balance determines the diversity of tie strengths. Our results provide insight into the driving mechanisms of tie strength heterogeneity in social networks and have implications for the understanding of social network structure and individual behavior.Description
Funding Information: G.I. thanks Tiina Näsi for valuable suggestions. G.I. and J.K. acknowledge support from AFOSR (Grant No. FA8655-20-1-7020), project EU H2020 Humane AI-net (Grant No. 952026), and CHIST-ERA project SAI (Grant No. FWF I 5205-N). J.K. acknowledges support from European Union’s Horizon 2020 research and innovation programme under grant agreement ERC No 810115 - DYNASNET. We acknowledge the computational resources provided by the Aalto Science–IT project. The study was part of the NetResilience consortium funded by the Strategic Research Council at the Academy of Finland (grant numbers 345188 and 345183). | openaire: EC/H2020/952026/EU//HumanE-AI-Net
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Iñiguez, G, Heydari, S, Kertész, J & Saramäki, J 2023, 'Universal patterns in egocentric communication networks', Nature Communications, vol. 14, no. 1, 5217, pp. 1-9. https://doi.org/10.1038/s41467-023-40888-5