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Assessment of Social Media Usage during Hurricane Sandy and the Development of a Twitter‐based, Web Application for Real‐time Communication of Storm‐related Information
32nd Conference on Environmental
Information Processing Technologies
New Orleans, Louisiana
January 11, 2016
John F. Edwards, Ph.D.
Somya D. Mohanty, Ph.D.
Patrick Fitzpatrick, Ph.D.
David Martin, B.S.
Introduction
Funding
•
National Oceanic and Atmospheric Administration
Coastal Storm Awareness Program
Connecticut Sea Grant
Objectives
•
Survey affected population regarding storm‐related communication
•
Identify and codify storm‐related messages from Twitter
•
Identify major “Influencers” disseminating weather‐related info
•
Develop a Twitter‐based, data collection and bidirectional communication system for weather‐related emergencies
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Survey Data
Telephone and Twitter‐based
Survey Sampling and Methods
Cell Phone Sampling Frame
Landline Sampling Frame
Phone Modality
(n=514)
Geo‐Coded Tweets (n=15,000)
Twitter‐Distributed Modality (n=179)
Survey Data
(n=693)
Survey Data
Catchment Area for both
Telephone and Twitter‐based Samples
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Survey Data
Loss of Power and Communication Mediums
Power
62%
Television
58%
Wired Internet
53%
Landline
45%
Cellphone
27%
0%
10%
20%
30%
40%
50%
60%
70%
Survey Data
Communication Mediums Relationship to Evacuation
60%
50%
53%
50%
40%
39%
30%
20%
25%
21%
19%
14%
10%
8%
0%
Evacuated (12%)
Face‐to‐Face
Television
14% 13%
7%
Prepared in Place (69%)
9%
Did Nothing (19%)
Telephone (Voice & Text)
Social Media
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Survey Data
Weather‐related Entities Followed on Twitter
Red Cross
4.3%
NOAA
6.5%
Local Radio
6.6%
Meterorologist
6.8%
FEMA
6.8%
TWC
10.3%
NWS
11.6%
Local News
13.0%
0.0%
2.0%
4.0%
6.0%
8.0%
10.0%
12.0%
14.0%
Survey Data
Type of Information Shared on Twitter
Photographs
62%
Personal Experiences
56%
Storm Damage
53%
Storm Warnings
47%
General Messages
47%
0%
10%
20%
30%
40%
50%
60%
70%
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Social Media Data 4.5 million Geo‐coded Tweets
Social Media Data Volume
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Social Media Data Sentiment
Social Media Data User Network – Pre
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Social Media Data User Network – During
Social Media Data User Network – Post
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Social Media Data
Identifying and Codifying
Pleading for Help
Offering Help
Organizing Help
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Software URL
Software
Codifier Module
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Software
Emergency Manager Module
Software
Data Collection Module
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Software
Example Image
Software
Example Image
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Software
Example Image
Software
Example Image
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Software
Example Image
Future of Using Human Sensors for Obtaining Weather‐Related Information
•
~150 million more Twitter users since Hurricane Sandy
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Posting photographs has become much easier and more commonplace. Twitter hosts photos natively.
•
Advances in natural language processing and image recognition will increase the efficiency of the software
•
We do not condone capturing photographs of dangerous weather activity, but our software allows such photographs to be used for a greater good. 13
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Questions
John F. Edwards, Ph.D.
je@ssrc.msstate.edu
662.325.9726
32nd Conference on Environmental
Information Processing Technologies
New Orleans, Louisiana
January 11, 2016
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