1. Data & UGC
for
(Natural) disaster
coverage
Rina Tsubaki
Emergency Journalism
European Journalism Centre
tsubaki@ejc.net

2. Emergency situations
speed
accuracy
consistency
responsiveness
simplicity of shared information

3. Information
=
aid
Preparedness
=
better information

4. Hurricane Sandy by WNYC

5. Hurricane Sandy by WNYC

6. Google Crisis Map
Hurricane Pablo (Bopha)

7. new meaning to “by the
people,
for the people”
A pathway for better
governance and public
services

8. Crowdsourcing: Risks
False & Fake
Rumors
Time-lag
Virality
Privacy

9. UGC = data?
Crowdsourcing is great but data is not solid.
Example: Boston Bombings
Sample:
-8 million unique tweets
-3.7 million unique users
-15-19 April 2013
Research: http://precog.iiitd.edu.in/Publications_files/ecrs2013_ag_hl_pk.pdf

10. UGC = data?
Crowdsourcing is great but data is not solid.
Example: Boston Bombings
-29% = rumors and fake content
-51% = generic opinions and comments
-20% = true information
-Verified accounts and users with high social reputation were
responsible for spreading the fake content

11. UGC = data?
Crowdsourcing is great but data is not solid.
Example: Boston Bombings
-32,000 new accounts with at least one tweet
-20 % of new accounts suspended by Twitter
-Some of the deleted accounts found to be ‘quite influential’.

12. False & fake
Hurricane Sandy photo
Real photo from the past event
Source: Mashable, 7 Fake Hurricane Sandy Photos You're Sharing on Social Media
http://mashable.com/2012/10/29/fake-hurricane-sandy-photos/

13. False & fake
Hurricane Sandy Photo
Intentionally tweaked photos
Source: Snopes.com ‘Hurricane Sandy Photographs’
http://www.snopes.com/photos/natural/sandy.asp

15. The role of journalists
& Aid Responders
Data Mining
Data Sharing
Data Visualisation
Verification
Navigation

16. Verification Handbook
verificationhandbook.com

17. Data Journalism handbook

18. Geofeedia: Tool to find UGC with
geo-location info