Utilizing Social Media to Understand Human Interaction with Extreme Media Events - The Superstorm Sandy Beta Test

1. 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

2. NASA-NOAA Suomi National Polar-orbiting Partnership (NPP) satellite

3. Twitter Flicker

4. Facebook

5. Twitter • Social Networking and micro-blogging service • Created in 2006 • 140 character tweets • 140+ million users /400 million tweets per day • Fast information propagation • Our Access: • Real-time Firehose – Instantaneous acquisition of tweets • Historical Track – Tweets since 2006

6. Extreme Events and Social Media • Traditional Methods • Telephone Survey • Invasive information acquisition • Twitter • 170 million active users worldwide • 48 million in U.S. • ~26 million geo-located “human sensors” • Passive information collection • Use Cases • Sandy Super-Storm • Moore Tornado

7. Tracking Tweets • Geographic Bounding Boxes • Hurricane or Tornado path • Keyword Searches • Complex searches on text within tweets • User Tracking • Tracking any tweets either made by a user or mentioning a user (i.e. @usNWSgov – National Weather Service twitter handle) • Hashtag Tracking • Tracking on topics (i.e. #sandy)

8. Advantages of Tracking Social Media • Network Resiliency • Mobile phone service is pretty resilient - in certain use cases traffic doubled • Real-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 recovery • Determine Human Mobility Patterns • Ability to help disaster recovery agencies assist before, after and during and event

9. Advantages of Tracking Social Media • Development of Predictive Algorithms • Utilizing historical data to create predictive models capable of detecting future events • Predicting the extent of damages as a result of an disaster • Help 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

10. Moore Tornado (OK) • 138K geo-coded tweets – May 15th – May 30th • Utilization • Structural analysis of buildings, roadsand infrastructure using posted pictures • Modeling predictive algorithms by extracting parameters consistent with tweets from affected areas • NSF Rapid Response Grant

11. Sandy SuperStorm • 4.8M Tweets - Oct 27th – Nov 14th 2012 • Utilization • Real-time visual monitoring of posted pictures • Traffic Analysis for Resiliency • Sub-Event Analysis – Power Outage • Topic Analysis – Keyword and Hashtag Clouds • Trend Analysis – Occurrence of events relative to others • Sentiment Analysis – Feedback of public opinion • U.S. Department of Health and Human Services • Office of the Assistant Secretary for Preparedness and Response • Collaboration with New Jersey Mayors office and Harvard Law School

12. Social Media Tracking and Analysis System SMTAS Hurricane Sandy Study

13. Public Sentiment for Relief AgenciesFollowing Hurricane Sandy

14. Organic Help Networks • Creating networks of help • Offers to help • Asking for help from organizations • Asking for help from followers

15. Creating Networksof Help

16. Offersfor help

17. Asking for help from organizations

18. Asking for help from followers

19. SMTAS @ Innovative Data Laboratory www.idl.ssrc.msstate.edu