http://aidr.qcri.org/

Muhammad Imran, Carlos Castillo, Ji Lucas, Patrick Meier, Sarah ViewegQatar Computing Research Institute (QCRI)

Doha, Qatar

AIDR: Artificial Intelligence for Disaster Response

http://aidr.qcri.org/

2013 Pakistan Earthquake: September 28 at 07:34 UTC 2010 Haiti Earthquake: January 12 at 21:53 UTC

CRISIS COMPUTING

…

Content generator Social Media Messages

CRISIS COMPUTING

http://aidr.qcri.org/

Apply machine learningApply crowdsourcing

CRISIS COMPUTING: CHALLENGES

http://aidr.qcri.org/

- High velocity (e.g., 16k tweets / minute during Sandy)- Redundant information (high volume of re-tweets)- Unstructured messages- Short text (140 characters in case of tweets)- Multilingual messages- Poor grammar

http://aidr.qcri.org/

AIDR —Artificial Intelligence for Disaster Response— is a free, open-source, and easy-to-use platform to automatically filter and classify relevant tweets posted during humanitarian crises.

ML+ CROWDSOURCING

http://aidr.qcri.org/

AIDR = Machine learning + Crowdsourcing

AIDR: FROM END-USERS PERSPECTIVE

Collection Classifier(s)

• Keywords, Hashtags• Geographical bounding box• Language• Follow specific set of users

A collection is a set of filters A classifier is a set of tags• Donations requests & offers• Damage & causalities• Eyewitness accounts

2 step approach1 2

http://aidr.qcri.org/

AIDR APPROACH

Collection Classifier(s)

Tag Tag

Tag Tag

Learner

Classifier-1

Tag

Tag Tag Tag

30k/min

Classifier-2

http://aidr.qcri.org/

AIDR – COLLECTION SETUPCollection detail dashboard

http://aidr.qcri.org/

Geographical region filterLanguage filter

Collection definition

http://aidr.qcri.org/

AIDR – CLASSIFIER SETUP

AIDR – CLASSIFIER SETUP (cont.)

http://aidr.qcri.org/

AIDR – CROWDSOURCING-1Internal Tagging Interface

http://aidr.qcri.org/

AIDR – CROWDSOURCING-2MicroMapper Interface (browser clicker)

http://aidr.qcri.org/

Mobile clicker

AIDR – OUTPUT

http://aidr.qcri.org/

Training examples Classified output (achieved accuracy ~ 75%)

AIDR – CLASSIFICATION USING RANDOM FOREST

http://aidr.qcri.org/

T1 T2 T3 Tn

Features

Category aCategory b

Data: predictors with known responseGoal: predict the response when it’s unknown (e.g., Hepatitis)

Protein < 45.43

V =

yesno

Protein >= 26

X <= p

http://aidr.qcri.org/

AIDR —Artificial Intelligence for Disaster Response— is a free, open-source, and easy-to-use platform to automatically filter and classify relevant tweets posted during humanitarian crises.

Thank you!