Show simple item record

dc.contributor.authorCebrian, Manuel
dc.contributor.authorLahiri, Mayank
dc.contributor.authorOliver, Nuria
dc.contributor.authorPentland, Alex Paul
dc.date.accessioned2011-12-13T21:25:56Z
dc.date.available2011-12-13T21:25:56Z
dc.date.issued2010-08
dc.date.submitted2009-10
dc.identifier.issn1932-4553
dc.identifier.otherINSPEC Accession Number: 11415794
dc.identifier.urihttp://hdl.handle.net/1721.1/67652
dc.description.abstractIn any society, is the way in which individuals interact, intentionally or unintentionally, designed to maximize global benefit, or does it result in a fundamentally non-egalitarian stratification of society, where a small number of individuals inevitably dominate? Our ability to observe and record interactions between individuals in real populations has improved dramatically with modern technological improvements, but it is still a difficult task to use this data to model cooperation and collaboration between individuals, and its global effect on the entire population. To shed light on these questions, we model an individual's value in society as an epistatic mathematical function of a set of binary choices, and the collective potential of a population as the expected value of an individual over time. Individuals try to selfishly improve their societal value by adopting the choices of their neighbors, constrained by the actual observed interaction topology and order. As a result, we are also able to investigate how far natural populations are from an optimal regime of functioning. We show that interaction topology has a large impact on collective potential, but the relative order of specific interactions seems to have a negligible effect.en_US
dc.language.isoen_US
dc.publisherInstitute of Electrical and Electronics Engineersen_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/jstsp.2010.2053093en_US
dc.rightsArticle 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.en_US
dc.sourceIEEEen_US
dc.titleMeasuring the Collective Potential of Populations From Dynamic Social Interaction Dataen_US
dc.typeArticleen_US
dc.identifier.citationCebrian, M. et al. “Measuring the Collective Potential of Populations From Dynamic Social Interaction Data.” IEEE Journal of Selected Topics in Signal Processing, 4.4 (2010): 677-686.© 2010 IEEE.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Media Laboratoryen_US
dc.contributor.departmentProgram in Media Arts and Sciences (Massachusetts Institute of Technology)en_US
dc.contributor.approverPentland, Alex Paul
dc.contributor.mitauthorPentland, Alex Paul
dc.contributor.mitauthorCebrian, Manuel
dc.relation.journalIEEE Journal of Selected Topics in Signal Processingen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.orderedauthorsCebrian, Manuel; Lahiri, Mayank; Oliver, Nuria; Pentland, Alexen
dc.identifier.orcidhttps://orcid.org/0000-0002-8053-9983
mit.licensePUBLISHER_POLICYen_US
mit.metadata.statusComplete


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record