ISCRAM 2013, May 12-15 1 PhaseVis: Visualizing the Four Phases of Emergency Management Through the Lens of Social Media Seungwon Yang et al. Department of Computer Science, Virginia Tech 5/13/2013

Outline 1. Motivation 2. Hurricane Isaac 3. Approach (Selection, Classification, Visualization) 4. PhaseVis in Action 5. Limitations 6. Discussion ISCRAM 2013, May 12-15 2 1. Motivation Four Phases of Emergency Management Model FEMA training material adds Prevention/Protection http://training.fema.gov/EMIWeb/IS/IS230B/IS230bCourse.pdf ISCRAM 2013, May 12-15 3 Response Recovery Mitigation Preparedne ss 2. Hurricane Isaac: Trajectory ISCRAM 2013, May 12-15 4 8/24 Cuba, Hispaniola: approx. 30 died 8/28-29 Mississippi River, Georgia, Port Fourchon, LA: 9 died After 8/30 N. Louisiana: degenerated to tropical depression *Image by Cyclonebiskit (Wikipedia) 8/21 Tropical storm Isaac 8/19-20 Extratropical cyclone ISCRAM 2013, May 12-15 5 Disaster Tweets with emergency orgs, agency names Visualiza on & Interac on Manual Labeling Training Data Trained classifica on model Cleaned Tweets Original Tweets Original & Retweets Classified Tweets Select and Preprocess Tweets Classify into 4 phases Implement visualization & interaction 3. Overall Approach Tweet collection using #isaac with yourTwapperKeeper Situation report & Information sharing Majority of tweets Embedded URLs: news webpages, videos, photographs Personal activity report Very few ISCRAM 2013, May 12-15 6 3. Tweet Collection Approx. 56,000 English tweets collected with #Isaac 5,677 tweets (10%) with reference to Red Cross, FEMA, or Salvation Army 1,453 non-retweets 1,121 manually labeled with one of four phases (response, recovery, mitigation, preparedness) ISCRAM 2013, May 12-15 7 3. Building a Dataset (1/2) Tweet text + resource title ISCRAM 2013, May 12-15 8 Nice article abt our Dir. Of emerg srvcs @leopratte in #Louisiana organizing #redcross #Isaac relief http://t.co/D4RPr33n 3. Building a Dataset (2/2) ISCRAM 2013, May 12-15 9 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 Preparednes s Very cool app! MT @redcross: Our hurricane app has info on #RedCross shelters, a toolkit w flashlight, alarm http://t.co/E7o1rtJK #Isaac 3. Examples of 4 Phases SVM multiclass with linear kernel Large num. of features, small num. of training examples Nave Bayes multinomial Bag-of-words model fits well for tweet data Random forest One of the robust algorithms for text classification ISCRAM 2013, May 12-15 10 3. Classification Algorithms TF, normalization, stemming applied Tuned classifier, 10 fold cross-validation ISCRAM 2013, May 12-15 11 Precision Weighted F Measure Nave Bayes multinomial 77.87% 0.782 Random forest 76.27% 0.754 SVM multiclass (linear kernel) 80.82% Reported slightly lower than Nave Bayes multinomial 3. Classification Cross-Validation ISCRAM 2013, May 12-15 12 3. Tweet Visualization WHAT WHEN WHERE WHO WHAT (Phases, List) Phases: ThemeRiver, D3 visualization toolkit Tweet List: JqGrid Library WHEN (Timeline) JavaScript WHERE (user locations) Google Maps API WHO (user mention network) Gephi graph format, Sigma.js ISCRAM 2013, May 12-15 13 3. Visualization Implementation ISCRAM 2013, May 12-15 14 4. PhaseVis in Action (8/23-8/24) Majority of tweets in Preparedness phase (84%) Content: fill up the gas tank, hurricane App, preparedness tips, replace food/water in emergency kit, etc Clustered around Red Cross, FEMA, & CraigatFEMA Study focus was rather on the US (English tweets) Spanish tweets from Cuba, Hispaniola not considered Unable to understand phases in such areas ISCRAM 2013, May 12-15 15 4. Summary (8/23-8/24) ISCRAM 2013, May 12-15 16 4. PhaseVis in Action (8/28-8/29) - Mainly in Louisiana, Mississippi, Georgia - High increase in tweet volume Isaac landed in the US in 8/28 with hurricane strength Response (20%), Recovery (34%), Mitigation (0%), Preparedness (46%) Content: Recruiting volunteers (Response, Recovery) Asking for donations/support (Recovery) RT regarding Mitt Romney Providing shelters (Response) ISCRAM 2013, May 12-15 17 4. Tweet Details (8/28-8/29) ISCRAM 2013, May 12-15 18 4. PhaseVis in Action (9/5-9/7) - US continued - Mostly Recovery phase (75%), followed by continued Response actions Lots of activities in New Orleans, Baton Rouge, Louisiana Active tweet account: FEMA, Red Cross, RedCrossSELA (South East Louisiana) ISCRAM 2013, May 12-15 19 4. Tweet Details (9/5-9/7) ISCRAM 2013, May 12-15 20 5. Limitations Language Only English tweets considered Unable to analyze Spanish tweets when Isaac hit Cuba & Hispaniola Small data set Only tweets containing FEMA, Red Cross & Salvation Army E.g., RedCrossSELA, SalvationArmy, craigatFEMA, Approx. 10% of tweets had those names ISCRAM 2013, May 12-15 21 6. Discussion What are other valuable information to uncover from disaster tweets and why are they important? Sentiment, Reliability of tweets Embedded URLs: news articles, images, videos ?? To what extent can tweet analysis actually help emergency managers in the field? Identification of actionable tweets from affected areas, victims, and witnesses ?? NSF for funding: IIS-0916733 (CTRnet project) Internet Archive for collaboration Big thanks to co-authors who couldnt come here Haeyong Chung, Xiao Lin, Sunshin Lee, Liangzhe Chen, Andy Wood, and the CTRnet Team ISCRAM 2013, May 12-15 22 Acknowledgment Thank you! Questions? ISCRAM 2013, May 12-15 23 Supplementary ISCRAM 2013, May 12-15 24 Evaluation Preprocessing & Accuracy ISCRAM 2013, May 12-15 25 TF IDF Normali zation Nave Bayes Multinomial SVM Multiclass 76% 80.1% X 77% 80.4% X 60% 78.8% X X 78.1% X 75% 80.4% X X 78% 80.8% X X 63% 78.9% X X X 79.0% ISCRAM 2013, May 12-15 26 3. Visualization: Phase View ISCRAM 2013, May 12-15 27 Overview Detail 3. Visualization: Social Network View ISCRAM 2013, May 12-15 28 3. Visualization: Location View ISCRAM 2013, May 12-15 29 Is_R (Retweet check) Tweet Text Phases Date 3. Visualization: Tweet View Use Case & Demo http://spare05.dlib.vt.edu/~ctrvis/phasevis/ind ex_may.html ISCRAM 2013, May 12-15 30 ISCRAM 2013, May 12-15 31 ISCRAM 2013, May 12-15 32