utilizing social media to understand human interaction with extreme media events - the superstorm ...
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Utilizing Social Media to Understand Human Interaction with Extreme Media Events - The Superstorm Sandy Beta Test. Arthur G. Cosby Somya D. Mohanty. National Weather Service Online Webinar Jul 16 , 2013. NASA-NOAA Suomi National Polar-orbiting Partnership (NPP) satellite. Twitter. - PowerPoint PPT PresentationTRANSCRIPT
Social Media Tracking & Analysis Software
Utilizing Social Media to Understand Human Interaction with Extreme Media Events -The Superstorm Sandy Beta TestArthur G. Cosby Somya D. Mohanty
National Weather ServiceOnline WebinarJul 16, 2013NASA-NOAA Suomi National Polar-orbiting Partnership (NPP) satelliteFlickerTwitterFacebook
TwitterSocial Networking and micro-blogging serviceCreated in 2006140 character tweets140+ million users /400 million tweets per dayFast information propagationOur Access:Real-time Firehose Instantaneous acquisition of tweetsHistorical Track Tweets since 2006
Extreme Events and Social MediaTraditional MethodsTelephone SurveyInvasive information acquisitionTwitter170 million active users worldwide48 million in U.S.~26 million geo-located human sensorsPassive information collectionUse CasesSandy Super-StormMoore TornadoTracking TweetsGeographic Bounding BoxesHurricane or Tornado pathKeyword SearchesComplex searches on text within tweetsUser TrackingTracking any tweets either made by a user or mentioning a user (i.e. @usNWSgov National Weather Service twitter handle)Hashtag TrackingTracking on topics (i.e. #sandy)Advantages of Tracking Social MediaNetwork ResiliencyMobile phone service is pretty resilient - in certain use cases traffic doubledReal-time Visual Monitoring Tracking of pictures posted of the event from twitter users via Instagram, Vine, etc.Identification of Sub-events Power Outages, Flooding, Disaster recoveryDetermine Human Mobility PatternsAbility to help disaster recovery agencies assist before, after and during and event
Advantages of Tracking Social MediaDevelopment of Predictive AlgorithmsUtilizing historical data to create predictive models capable of detecting future eventsPredicting the extent of damages as a result of an disasterHelp and Assist Information Propagation Developing organic networks in case of an event need real-time information feedback.Prevent Incorrect Information Dissemination Analyzing the information disseminated by the users of the network for their validity in context to an event
Moore Tornado (OK)138K geo-coded tweets May 15th May 30thUtilizationStructural analysis of buildings, roads and infrastructure using posted picturesModeling predictive algorithms by extracting parameters consistent with tweets from affected areasNSF Rapid Response Grant
Sandy SuperStorm4.8M Tweets - Oct 27th Nov 14th 2012UtilizationReal-time visual monitoring of posted picturesTraffic Analysis for ResiliencySub-Event Analysis Power OutageTopic Analysis Keyword and Hashtag CloudsTrend Analysis Occurrence of events relative to othersSentiment Analysis Feedback of public opinionU.S. Department of Health and Human Services Office of the Assistant Secretary for Preparedness and ResponseCollaboration with New Jersey Mayors office and Harvard Law School
Hurricane Sandy StudySocial Media Tracking and Analysis System SMTAS
Public Sentiment for Relief AgenciesFollowing Hurricane Sandy
Organic Help NetworksCreating networks of helpOffers to helpAsking for help from organizationsAsking for help from followersCreating Networksof HelpOffersfor helpAsking for help from organizationsAsking for help from followersSMTAS @ Innovative Data Laboratory
www.idl.ssrc.msstate.edu