Analyzing and Visualizing Disaster Phases from Social Media
Analyzing and Visualizing Disaster Phases from Social Media Streams Group VizDisasters: Liangzhe Chen, Xaio Lin, Andrew Wood Client: Seungwon Yang Information Storage & Retrieval Final Presentation 12/4/2012 Virginia Tech Motivation CTRnet: archiving disaster-related online data in collaboration with the Internet Archive Tweets during disasters: quick alternative to
cell phones Large dataset to pull from for researchers & responders Four Phases of Emergency Management Four phases: Response Recovery Mitigation Preparedness Professional and personal activities Four Phases in Tweets Reporting situation / sharing information Majority
For hurricane: rain, flood, wind, cloud, weather forecast Photographs (Instagram) Reporting personal activities Very few 02/11/2020 ProjVisDisaster 4 Four Phases in Tweets Reporting professional activities Response
More than 4,700 people in as many as 80 shelters in 7 states overnight; more than 3,000 #RedCross workers (37 from KC region) at #Isaac Recovery FEMA announces that federal aid has been made available for the state of Louisiana. #Isaac Mitigation FEMA mitigations advisers to offer rebuilding tips in St. Bernard and Ascension Parishes. http://t.co/ZziRGOGw #Isaac Preparedness Very cool app! MT @redcross: Our hurricane app has info on #RedCross shelters, a toolkit w flashlight, alarm http://t.co/E7o1rtJK #Isaac 02/11/2020
ProjVisDisaster 5 Our Approach 02/11/2020 ProjVisDisaster 6 Our Approach Machine learning Extract professional activities Classify professional activities into four phases
Visualization Phase view, tweet view, social network view, map view Use case / Demo 02/11/2020 ProjVisDisaster 7 Learning Professional Activities in Four Phases
02/11/2020 ProjVisDisaster 8 Learning Professional Activities in Four Phases Preprocessing Building dataset Vectorization Classification
Algorithms Evaluation 02/11/2020 ProjVisDisaster 9 Building dataset Focus on tweets about professional activities Based on keywords of known organizations FEMA Red Cross (RedCross) Salvation Army (SalvationArmy)
02/11/2020 ProjVisDisaster 10 Building dataset Combining tweet and resource title Mitigation specialists are offering free rebuilding tips in five parishes. http://t.co/hwXajm6X #Isaac 02/11/2020 ProjVisDisaster 11
Building dataset Overview of Issac dataset About 56,000 English tweets during hurricane Issac 5,677 tweets with reference to FEMA, Red Cross or Salvation Army 1,453 without re-tweets 1,121 manually labeled explicitly with one of the four phases, response, recovery, mitigation or preparedness 02/11/2020 ProjVisDisaster 12
ProjVisDisaster 22 Use Case & Demo http://spare05.dlib.vt.edu/~ctrvis/phasevis/ 02/11/2020 ProjVisDisaster 23 Use Case
02/11/2020 ProjVisDisaster 24 Use Case 02/11/2020 ProjVisDisaster 25 Summary and Future Work Summary:
Analysis/classification of disaster tweets into phases Multi-view visualization Future challenges: Automated professional organization extraction Processing of personal tweets Application to other disasters 02/11/2020 ProjVisDisaster 26 Acknowledgements Haeyong Chung
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