Full metadata record
DC Field | Value | Language |
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dc.contributor.author | Bauman, Konstantin | - |
dc.contributor.author | Tuzhilin, Alexander | - |
dc.contributor.author | Zaczynski, Ryan | - |
dc.date.accessioned | 2015-09-01T14:48:48Z | - |
dc.date.available | 2015-09-01T14:48:48Z | - |
dc.date.issued | 2015-09-01 | - |
dc.identifier.uri | http://hdl.handle.net/2451/34226 | - |
dc.description.abstract | In 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.sponsorship | NYU Stern School of Business | en_US |
dc.language.iso | en_US | en_US |
dc.relation.ispartofseries | ;CBA-15-03 | - |
dc.title | Virtual Power Outage Detection Using Social Sensors | en_US |
dc.type | Working Paper | en_US |
Appears in Collections: | Center for Business Analytics Working Papers |
Files in This Item:
File | Description | Size | Format | |
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virtual_power_outage.pdf | 276.99 kB | Adobe PDF | View/Open |
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