Fundamental structures of dynamic social networks
Name
Sekara-2016-Fundamental structur.pdf
Size
1.25 MB
Format
Adobe PDF
Checksum (MD5)
b20fe0585711baa2181e5751d29a787d
Author(s)
Sekara, Vedran
Stopczynski, Arkadiusz
Lehmann, Sune
Date Issued
August 2016
Journal
Proceedings of the National Academy of Sciences
Publisher
National Academy of Sciences (U.S.)
Citation
Sekara, Vedran; Stopczynski, Arkadiusz and Lehmann, Sune. “Fundamental Structures of Dynamic Social Networks.” Proceedings of the National Academy of Sciences 113, no. 36 (August 2016): 9977–9982. © 2016 National Academy of Sciences
Version
Final published version
Abstract
Social systems are in a constant state of flux, with dynamics spanning from minute-by-minute changes to patterns present on the timescale of years. Accurate models of social dynamics are important for understanding the spreading of influence or diseases, formation of friendships, and the productivity of teams. Although there has been much progress on understanding complex networks over the past decade, little is known about the regularities governing the microdynamics of social networks. Here, we explore the dynamic social network of a densely-connected population of ∼1,000 individuals and their interactions in the network of real-world person-to-person proximity measured via Bluetooth, as well as their telecommunication networks, online social media contacts, geolocation, and demographic data. These high-resolution data allow us to observe social groups directly, rendering community detection unnecessary. Starting from 5-min time slices, we uncover dynamic social structures expressed on multiple timescales. On the hourly timescale, we find that gatherings are fluid, with members coming and going, but organized via a stable core of individuals. Each core represents a social context. Cores exhibit a pattern of recurring meetings across weeks and months, each with varying degrees of regularity. Taken together, these findings provide a powerful simplification of the social network, where cores represent fundamental structures expressed with strong temporal and spatial regularity. Using this framework, we explore the complex interplay between social and geospatial behavior, documenting how the formation of cores is preceded by coordination behavior in the communication networks and demonstrating that social behavior can be predicted with high precision.
MIT Department
Massachusetts Institute of Technology. Media Laboratory
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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DOI of Published Version
https://doi.org/10.1073/pnas.1602803113
