Usability of small crisis data sets in the absence of big data
Contribuinte(s) |
Ariwa, Ezendu Zhao, Wenbing Gandhi, Meenakshi |
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Data(s) |
14/03/2013
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Resumo |
Big data is big news in almost every sector including crisis communication. However, not everyone has access to big data and even if we have access to big data, we often do not have necessary tools to analyze and cross reference such a large data set. Therefore this paper looks at patterns in small data sets that we have ability to collect with our current tools to understand if we can find actionable information from what we already have. We have analyzed 164390 tweets collected during 2011 earthquake to find out what type of location specific information people mention in their tweet and when do they talk about that. Based on our analysis we find that even a small data set that has far less data than a big data set can be useful to find priority disaster specific areas quickly. |
Formato |
application/pdf |
Identificador | |
Publicador |
Atlantis Press |
Relação |
http://eprints.qut.edu.au/58830/1/M1249.pdf DOI:10.2991/icibet.2013.248 Paul, Avijit & Bruns, Axel (2013) Usability of small crisis data sets in the absence of big data. In Ariwa, Ezendu, Zhao, Wenbing, & Gandhi, Meenakshi (Eds.) Proceedings of the 2013 International Conference on Information, Business and Education Technology, Atlantis Press, Beijing, China, pp. 718-721. http://purl.org/au-research/grants/ARC/DP1094281 |
Direitos |
© 2013. The authors - Published by Atlantis Press Atlantis Press. This article is distributed under the terms of the Creative Commons Attribution License, which permits non-commercial use, distribution and reproduction in any medium, provided the original work is properly cited. |
Fonte |
ARC Centre of Excellence for Creative Industries and Innovation; Centre for Emergency & Disaster Management; Creative Industries Faculty; Institute for Creative Industries and Innovation; School of Media, Entertainment & Creative Arts |
Palavras-Chave | #080109 Pattern Recognition and Data Mining #200100 COMMUNICATION AND MEDIA STUDIES #Crisis Communication #Big Data #Twitter #Location |
Tipo |
Conference Paper |