1. Typhoon Haiyan
Analysis
Prepared for Humanity Road by ASU

2. Overview
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Category 5 “Super Typhoon”
Made Landfall in Philippines on November 7,
2013
Over 4000 fatalities confirmed so far
Data used in this report was collected using
TweetTracker* from ASU.
*http://tweettracker.fulton.asu.edu/

3. Dataset Statistics
Property
Value
No. Tweets
609,453
Avg. Tweet Length (characters)
83.97
No. Retweets
192,339 (31.6%)
No. Geotagged Tweets
303,301 (49.8%)
No. Unique Users
172,600
No. URLs
50,161
No. Unique Hashtags
25,123
No. Unique Mentioned Users
64,576
First Tweet
Thu Nov 07 09:00:43 MST 2013
Last Tweet
Sat Nov 09 10:13:38 MST 2013

4. Overall Trend Analysis
General Trend of all tweets discussing the Typhoon.
Red vertical line indicates start of storm.

5. “Tacloban” Trend

6. “Unicef” Trend

7. Client Analysis
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Studied the software users employ to tweet.
Compared mobile and non-mobile clients.

8. Mobile Client Trend

9. Keyword Analysis
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Word cloud of top words used in disaster.
Larger words occur more often in the time period.
Tag cloud of entire dataset.
Tag cloud from the hour of landfall.

10. Geographic Analysis
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Analyze location of geolocated tweets.
Gives an understanding of where tweets are coming from.
Landfall
24 Hours After Landfall
48 Hours After Landfall

11. Authors
Fred Morstatter
Shamanth Kumar
Mark Karlsrud
Daniel Howe
Grant Marshall
Data Mining and Machine Learning Lab at ASU