Twitter Disaster Behavior

dc.contributor.authorThackaberry, Tayloren
dc.contributor.authorBogemann, Kayleyen
dc.contributor.authorBurchard, Shaneen
dc.contributor.authorButler, Jessieen
dc.contributor.authorSpencer, Austinen
dc.date.accessioned2020-05-13T19:31:55Zen
dc.date.available2020-05-13T19:31:55Zen
dc.date.issued2020-05-05en
dc.description.abstractThe purpose of the Twitter Disaster Behavior project is to identify patterns in online behavior during natural disasters by analyzing Twitter data. The main goal is to better understand the needs of a community during and after a disaster, to aid in recovery. The datasets analyzed were collections of tweets about Hurricane Maria, and recent earthquake events, in Puerto Rico. All tweets pertaining to Hurricane Maria are from the timeframe of September 15 through October 14, 2017. Similarly, tweets pertaining to the Puerto Rico earthquake from January 7 through February 6, 2020 were collected. These tweets were then analyzed for their content, number of retweets, and the geotag associated with the author of the tweet. We counted the occurrence of key words in topics relating to preparation, response, impact, and recovery. This data was then graphed using Python and Matplotlib. Additionally, using a Twitter crawler, we extracted a large dataset of tweets by users that used geotags. These geotags are used to examine location changes among the users before, during, and after each natural disaster. Finally, after performing these analyses, we developed easy to understand visuals and compiled these figures into a poster. Using these figures and graphs, we compared the two datasets in order to identify any significant differences in behavior and response. The main differences we noticed stemmed from two key reasons: hurricanes can be predicted whereas earthquakes cannot, and hurricanes are usually an isolated event whereas earthquakes are followed by aftershocks. Thus, the Hurricane Maria dataset experienced the highest amount of tweet activity at the beginning of the event and the Puerto Rico earthquake dataset experienced peaks in tweet activity throughout the entire period, usually corresponding to aftershock occurrences. We studied these differences, as well as other important trends we identified.en
dc.description.notesISCRAMposterTwitterDisasterBehavior - Poster submission for the ISCRAM 2020 conference. TwitterDisasterBehavior_FinalPresentation - Powerpoint slides for the final presentation of the research TwitterDisasterBehavior_FinalReport - Final Report on the work done and conclusions drawn from the research TwitterDisasterBehavior_Figures - A collection of additional figures and graphs generated during researchen
dc.description.sponsorshipNational Science Foundationen
dc.description.sponsorshipCMMI-1638207en
dc.description.sponsorshipCRISP: Collaborative Research: Coordinated, Behaviorally-Aware Recovery for Transportation and Power Disruptionsen
dc.description.sponsorshipGlobal Event and Trend Archive Research (GETAR)en
dc.description.sponsorshipNSF IIS-1619028en
dc.identifier.urihttp://hdl.handle.net/10919/98251en
dc.language.isoen_USen
dc.publisherVirginia Techen
dc.relation.ispartof2020 International Association for Information Systems for Crisis Response and Managementen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectPuerto Ricoen
dc.subjectearthquakeen
dc.subjectHurricane Mariaen
dc.subjectTopic Analysisen
dc.subjectgeotagen
dc.subjectgeolocationen
dc.subjectsocial mediaen
dc.subjecttwitteren
dc.subjectdisasteren
dc.subjectbehavioren
dc.titleTwitter Disaster Behavioren
dc.typeImageen
dc.typePosteren
dc.typePresentationen
dc.typeReporten

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