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dc.contributor.authorStopczynski, Arkadiusz
dc.contributor.authorPentland, Alex Sandy’
dc.contributor.authorLehmann, Sune
dc.date.accessioned2021-10-27T20:11:06Z
dc.date.available2021-10-27T20:11:06Z
dc.date.issued2018
dc.identifier.urihttps://hdl.handle.net/1721.1/135176
dc.description.abstract© 2018, The Author(s). Social interactions among humans create complex networks and – despite a recent increase of online communication – the interactions mediated through physical proximity remain a fundamental way for people to connect. A common way to quantify the nature of the links between individuals is to consider repeated interactions: frequently occurring interactions indicate strong ties, such as friendships, while ties with low weights can indicate random encounters. Here we focus on a different dimension: rather than the strength of links, we study physical distance between individuals when a link is activated. The findings presented here are based on a dataset of proximity events in a population of approximately 500 individuals. To quantify the impact of the physical proximity on the dynamic network, we use a simulated epidemic spreading processes in two distinct networks of physical proximity. We consider the network of short-range interactions defined as d ≲ 1 meter, and the long-range which includes all interactions d ≲ 10 meters. Since these two networks arise from the same set of underlying behavioral data, we are able to quantitatively measure how the specific definition of the proximity network – short-range versus long-range – impacts the resulting network structure as well as spreading dynamics in epidemic simulations. We find that the short-range network – consistent with the literature – is characterized by densely-connected neighborhoods bridged by weak ties. More surprisingly, however, we show that spreading in the long-range network is quite different, mainly shaped by spurious interactions.
dc.language.isoen
dc.publisherSpringer Nature
dc.relation.isversionof10.1038/S41598-018-36116-6
dc.rightsCreative Commons Attribution 4.0 International license
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.sourceScientific Reports
dc.titleHow Physical Proximity Shapes Complex Social Networks
dc.typeArticle
dc.contributor.departmentMassachusetts Institute of Technology. Media Laboratory
dc.relation.journalScientific Reports
dc.eprint.versionFinal published version
dc.type.urihttp://purl.org/eprint/type/JournalArticle
eprint.statushttp://purl.org/eprint/status/PeerReviewed
dc.date.updated2019-07-26T17:24:06Z
dspace.orderedauthorsStopczynski, A; Pentland, AS; Lehmann, S
dspace.date.submission2019-07-26T17:24:08Z
mit.journal.volume8
mit.journal.issue1
mit.metadata.statusAuthority Work and Publication Information Needed


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