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dc.contributor.authorAltshuler, Yaniv
dc.contributor.authorShmueli, Erez
dc.contributor.authorZyskind, Guy
dc.contributor.authorLederman, Oren
dc.contributor.authorOliver, Nuria
dc.contributor.authorPentland, Alex
dc.date.accessioned2021-10-27T20:04:12Z
dc.date.available2021-10-27T20:04:12Z
dc.date.issued2014
dc.identifier.urihttps://hdl.handle.net/1721.1/134260
dc.description.abstract© 2014 IEEE. Optimizing the use of available resources is one of the key challenges in activities that consist of interactions with a large number of "target individuals," with the ultimate goal of "winning" as many of them as possible, such as in marketing, service provision, political campaigns, or homeland security. Typically, the cost of interactions is monotonically increasing such that a method for maximizing the performance of these campaigns is required. In this paper, we propose a mathematical model to compute an optimized campaign by automatically determining the number of interacting units and their type, and how they should be allocated to different geographical regions in order to maximize the campaign's performance. We validate our proposed model using real world mobility data.
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.relation.isversionof10.1109/TCSS.2014.2377831
dc.rightsCreative Commons Attribution-Noncommercial-Share Alike
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/
dc.sourceMIT web domain
dc.titleCampaign Optimization Through Behavioral Modeling and Mobile Network Analysis
dc.typeArticle
dc.identifier.citationAltshuler, Y., et al. "Campaign Optimization through Behavioral Modeling and Mobile Network Analysis." IEEE Transactions on Computational Social Systems 1 2 (2014): 121-34.
dc.contributor.departmentMassachusetts Institute of Technology. Media Laboratory
dc.relation.journalIEEE Transactions on Computational Social Systems
dc.eprint.versionAuthor's final manuscript
dc.type.urihttp://purl.org/eprint/type/JournalArticle
eprint.statushttp://purl.org/eprint/status/PeerReviewed
dc.date.updated2019-07-26T13:54:09Z
dspace.orderedauthorsAltshuler, Y; Shmueli, E; Zyskind, G; Lederman, O; Oliver, N; Pentland, A
dspace.date.submission2019-07-26T13:54:11Z
mit.journal.volume1
mit.journal.issue2
mit.metadata.statusAuthority Work and Publication Information Needed


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