Exploiting Geolocation, User and Temporal Information for Natural Hazards Monitoring in Twitter

  1. Víctor Fresno
  2. Arkaitz Zubiaga
  3. Heng Ji
  4. Raquel Martínez
Revue:
Procesamiento del lenguaje natural

ISSN: 1135-5948

Année de publication: 2015

Número: 54

Pages: 85-92

Type: Article

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D'autres publications dans: Procesamiento del lenguaje natural

Résumé

Cuando se producen eventos relacionados con situaciones de emergencia, es importante acceder a tanta información como sea posible relacionada con dicho evento. En este contexto algunas redes sociales como Twitter suponen un importante recurso de información en tiempo real. La técnicas clásicas de filtrado de información suelen centrarse en el análisis de coocurrencia de términos con el conjunto de palabras clave inicialmente consideradas. Sin embargo, estas aproximaciones pueden perder información, ya que no son capaces de recuperar información relevante que venga expresada con palabras que no coocurran con las palabras clave inicialmente usadas, y que expresan nuestra necesidad de información. Considerar información de geolocalización, usuario o temporal dentro de un enfoque de pseudo-relevance feedback, nos permite encontrar terminología relacionada con el evento, pero no coocurrente con las palabras clave inicialmente consideradas. Por otro lado, considerando el aspecto temporal se puede modificar una función de expansión de consultas como la divergencia de Kullback-Leibler con el fin de mejorar el filtrado de información en estas situaciones de emergencia. Nuestras propuestas se han evaluado en dos colecciones de eventos del mundo real obteniéndose resultados alentadores.

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Financeurs

  • U.S. Army Research Laboratory
    • W911NF-09-2-0053
  • Norfolk Southern

Références bibliographiques

  • Carpineto, C., R. de Mori, G. Romano, and B. Bigi. 2001. An information-theoretic approach to automatic query expansion. ACM Trans. Inf. Syst., 19(1):1-27.
  • De Longueville, B., R.S. Smith, and G. Luraschi. 2009. OMG, from here, i can see the ames!: A use case of mining location based social networks to acquire spatiotemporal data on forest fires. In Proceedings of the 2009 International Workshop on Location Based Social Networks, LBSN '09, pages 73{80, New York, NY, USA. ACM.
  • Deerwester, S., S.T. Dumais, G.W. Furnas, T.K. Landauer, and R. Harshman. 1990. Indexing by latent semantic analysis. Journal of the American society for information science, 41(6):391-407.
  • Hiemstra, D. 2009. Information Retrieval Models. Information Retrieval: Searching in the 21st Century, Wiley.
  • Hughes, A.L. and L. Palen. 2009. Twitter adoption and use in mass convergence and emergency events. International Journal of Emergency Management, 6(3):248-260.
  • Imran, M., C. Castillo, F. Diaz, and S. Vieweg. 2014. Processing social media messages in mass emergency: A survey. CoRR, abs/1407.7071.
  • Kullback, S. and R.A. Leibler. 1951. On information and sufficiency. Ann. Math. Statist., 22(1):79-86.
  • Mills, A., R. Chen, J. Lee, and H. R. Rao. 2009. Web 2.0 emergency applications: How useful can twitter be for emergency response. Journal of Information Privacy and Security, 5:3-26.
  • Palen, L., K. Anderson, G. Mark, J. Martin, D. Sicker, and D. Grunwald. 2010. A vision for technology-mediated public participation and assistance in mass emergencies and disasters. In The University of Edinburgh, editor, International Academic Research Conference, 14-16 April.
  • Sakaki, T., M. Okazaki, and Y. Matsuo. 2010. Earthquake shakes twitter users: real-time event detection by social sensors. In Proceedings of the 19th international conference on World wide web, pages 851-860. ACM.
  • Sasaki, K., S. Nagano, K. Ueno, and K. Cho. 2012. Feasibility study on detection of transportation information exploiting twitter as a sensor. In Sixth International AAAI Conference on Weblogs and Social Media. Workshop on When the City Meets the Citizen, AAAI Technical Report WS-12-04.
  • Schnebele, E. and G. Cervone. 2013. Improving remote sensing ood assessment using volunteered geographical data. Na- tural Hazards and Earth System Science, 13(3):669-677.
  • Shinohara, M., A. Hattori, S. Ioroi, H. Tanaka, H. Hayami, H. Fujioka, and Y. Harada. 2011. Design and trial of a cellphone-based hazard information sharing system for residents living close to an incident. In Next Generation Mobile Applications, Services and Technologies (NGMAST), 2011 5th International Conference on, pages 13-18, Sept.
  • Shklovski, I., L. Palen, and J. Sutton. 2008. Finding community through information and communication technology in disaster events. In Proceedings of the ACM 2008 Conference on Computer Supported Cooperative Work (CSCW 2008, pages 127-136.
  • Sinnappan, S., C. Farrell, and E. Stewart. 2010. Priceless tweets! a study on twitter messages posted during crisis: Black saturday. In Proceedings of Information Systems: De ning and Establishing a High Impact Discipline, number 39, Brisbane, Australia, 01-03 December 2010. 21st International Conference on Information Systems (ACIS 2010).
  • Sorensen, J.H. and B. Sorensen. 2007. Community processes: Warning and evacuation. In Handbook of Disaster Research, Handbooks of Sociology and Social Research. Springer New York, pages 183-199.
  • Starbird, K., L. Palen, A.L. Hughes, and S. Vieweg. 2010. Chatter on the red: What hazards threat reveals about the social life of microblogged information. In Proceedings of the 2010 ACM Conference on Computer Supported Cooperative Work, CSCW '10, pages 241-250, New York, NY, USA. ACM.
  • Steyvers, M. and T. Griffiths, 2007. Latent Semantic Analysis: A Road to Meaning, chapter Probabilistic topic models. Erlbaum, L.
  • Sutton, J., L. Palen, and I. Shklovki. 2008. Backchannels on the front lines: Emergent use of social media in the 2007 southern california fires. In Proceedings of the 2008 Information Systems for Crisis Response and Management Conference (ISCRAM 2008), pages 624-631, Washington, D.C.
  • Vieweg, S., A.L. Hughes, K. Starbird, and L. Palen. 2010. Microblogging during two natural hazards events: what twitter may contribute to situational awareness. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pages 1079-1088. ACM.
  • Xu, J. and W.B. Croft. 1996. Query expansion using local and global document analysis. In Proceedings of SIGIR 96, pa- ges 4-11, Zurich. ACM.
  • Zubiaga, A., D. Spina, V. Fresno, and R. Martínez. 2011. Classifying trending topics: a typology of conversation triggers on twitter. In C. Macdonald, I. Ounis, and I. Ruthven, editors, CIKM, pages 2461-2464. ACM.
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