Enhancing resilience to disasters using social media

During the last decade, Social Media (SM) have emerged as a prominent trend in social communication, with online platforms such as Facebook and Twitter to conquer the internet space with millions of visitors per day. SM usage generates an astonishing amount of information, which could be used for scarcely experienced situations, such as mass convergence and emergency events. This study presents a preliminary exploratory analysis on examining the capacity of Social Media to extract information on individuals choices during evacuation. We collect tweets from the evacuation in Oroville, California USA due to danger of flood and the evacuation. The data is used for the creation of a user sample which allows the collection of historical data The historical data is compared with the data collected during and after the evacuation. The goal of this comparison is the extraction of potential information related to the evacuation.

[1]  Dave Yates,et al.  Emergency knowledge management and social media technologies: A case study of the 2010 Haitian earthquake , 2011, Int. J. Inf. Manag..

[2]  Yong Gao,et al.  Uncovering Patterns of Inter-Urban Trip and Spatial Interaction from Social Media Check-In Data , 2013, PloS one.

[3]  Bin Jiang,et al.  The Evolution of Natural Cities from the Perspective of Location-Based Social Media , 2014, Digital Social Networks and Travel Behaviour in Urban Environments.

[4]  Hans-Peter Kriegel,et al.  A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise , 1996, KDD.

[5]  Francisco C. Pereira,et al.  Using Data From the Web to Predict Public Transport Arrivals Under Special Events Scenarios , 2015, J. Intell. Transp. Syst..

[6]  Serge P. Hoogendoorn,et al.  A review on travel behaviour modelling in dynamic traffic simulation models for evacuations , 2012 .

[7]  Constantinos Antoniou,et al.  Use of Geotagged Social Media in Urban Settings: Empirical Evidence on Its Potential from Twitter , 2015, 2015 IEEE 18th International Conference on Intelligent Transportation Systems.

[8]  Geert-Jan Houben,et al.  Twitcident: fighting fire with information from social web streams , 2012, WWW.

[9]  John M. Rose,et al.  Understanding household evacuation decisions using a stated choice survey: case study of bush fires , 2005 .

[10]  B. Lindsay.  Social Media and Disasters: Current Uses, Future Options, and Policy Considerations , 2011 .

[11]  Bob Edwards,et al.  Heading for higher ground: factors affecting real and hypothetical hurricane evacuation behavior , 2000 .

[12]  Guillaume Leduc,et al.  Road Traffic Data: Collection Methods and Applications , 2008 .

[13]  D. Dosa,et al.  A comparison of the nursing home evacuation experience between hurricanes katrina (2005) and gustav (2008). , 2009, Journal of the American Medical Directors Association.

[14]  George A. Miller,et al.  WordNet: A Lexical Database for English , 1995, HLT.

[15]  Earl J. Baker,et al.  Hurricane Evacuation Behavior , 1991, International Journal of Mass Emergencies & Disasters.

[16]  Bin Ran,et al.  Dynamic Origin-Destination Travel Demand Estimation Using Location Based Social Networking Data , 2014 .

[17]  Jure Leskovec,et al.  Friendship and mobility: user movement in location-based social networks , 2011, KDD.

[18]  Constantinos Antoniou,et al.  Mapping Social Media for Transportation Studies , 2016, IEEE Intelligent Systems.

[19]  Susan Grant-Muller,et al.  The Impact of Social Media Usage on Transport Policy: Issues, Challenges and Recommendations☆ , 2014 .

[20]  Carlo Ratti,et al.  Understanding individual mobility patterns from urban sensing data: A mobile phone trace example , 2013 .

[21]  Susan L Handy,et al.  METHODOLOGIES FOR EXPLORING THE LINK BETWEEN URBAN FORM AND TRAVEL BEHAVIOR , 1996 .

[22]  Huiji Gao,et al.  Harnessing the Crowdsourcing Power of Social Media for Disaster Relief , 2011, IEEE Intelligent Systems.

[23]  David V. Canter,et al.  The decision to evacuate: a study of the motivations which contribute to evacuation in the event of fire , 1985 .

[24]  Axel Schulz,et al.  I See a Car Crash: Real-Time Detection of Small Scale Incidents in Microblogs , 2013, ESWC.

[25]  Dimitrios Efthymiou,et al.  Use of Social Media for Transport Data Collection , 2012 .

[26]  Yi Fang,et al.  Where not to go?: detecting road hazards using twitter , 2014, SIGIR.