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dc.contributor.authorBauman, Konstantin-
dc.contributor.authorTuzhilin, Alexander-
dc.contributor.authorZaczynski, Ryan-
dc.date.accessioned2015-09-01T14:48:48Z-
dc.date.available2015-09-01T14:48:48Z-
dc.date.issued2015-09-01-
dc.identifier.urihttp://hdl.handle.net/2451/34226-
dc.description.abstractIn this paper we describe a novel approach to detecting power outages that utilizes social media platform users as “social sensors” for virtual detection of power outages. We present the underlying methodology based on analyzing Twitter and other social media data that detects bursts in tweets related to the power outages. The proposed methodology was implemented and deployed by a major company in the area of enterprise solutions for social media aggregation for the electrical utility industry as a part of their comprehensive social engagement platform. It was also field tested on the Twitter users in an industrial setting and performed well during these tests.en_US
dc.description.sponsorshipNYU Stern School of Businessen_US
dc.language.isoen_USen_US
dc.relation.ispartofseries;CBA-15-03-
dc.titleVirtual Power Outage Detection Using Social Sensorsen_US
dc.typeWorking Paperen_US
Appears in Collections:Center for Business Analytics Working Papers

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