Twitter mining for disaster response: A domain adaptation approach

Hongmin Li, Nicolais Guevara, Nic Herndon, Doina Caragea, Kishore Neppalli, Cornelia Caragea, Anna Squicciarini, Andrea H. Tapia

Research output: Chapter in Book/Report/Conference proceedingConference contribution

27 Scopus citations

Abstract

Microblogging data such as Twitter data contains valuable information that has the potential to help improve the speed, quality, and efficiency of disaster response. Machine learning can help with this by prioritizing the tweets with respect to various classification criteria. However, supervised learning algorithms require labeled data to learn accurate classifiers. Unfortunately, for a new disaster, labeled tweets are not easily available, while they are usually available for previous disasters. Furthermore, unlabeled tweets from the current disaster are accumulating fast. We study the usefulness of labeled data from a prior source disaster, together with unlabeled data from the current target disaster to learn domain adaptation classifiers for the target. Experimental results suggest that, for some tasks, source data itself can be useful for classifying target data. However, for tasks specific to a particular disaster, domain adaptation approaches that use target unlabeled data in addition to source labeled data are superior.

Original languageEnglish (US)
Title of host publicationISCRAM 2015 Conference Proceedings - 12th International Conference on Information Systems for Crisis Response and Management
EditorsLeysia A. Palen, Tina Comes, Monika Buscher, Amanda Lee Hughes, Leysia A. Palen
PublisherInformation Systems for Crisis Response and Management, ISCRAM
ISBN (Electronic)9788271177881
StatePublished - 2015
Event12th International Conference on Information Systems for Crisis Response and Management, ISCRAM 2015 - Kristiansand, Norway
Duration: May 24 2015May 27 2015

Publication series

NameISCRAM 2015 Conference Proceedings - 12th International Conference on Information Systems for Crisis Response and Management
Volume2015-January

Other

Other12th International Conference on Information Systems for Crisis Response and Management, ISCRAM 2015
CountryNorway
CityKristiansand
Period5/24/155/27/15

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Electrical and Electronic Engineering
  • Information Systems and Management
  • Computer Networks and Communications

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