Usability of small crisis data sets in the absence of big data

& (2013) Usability of small crisis data sets in the absence of big data. In Zhao, W, Ariwa, E, & Gandhi, M (Eds.) Proceedings of the International Conference on Information, Business and Education Technology (ICIBIT 2013). Atlantis Press, China, pp. 718-721.

View at publisher

Description

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.

Impact and interest:

1 citations in Web of Science®
Search Google Scholar™

Citation counts are sourced monthly from Scopus and Web of Science® citation databases.

These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.

Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

Full-text downloads:

259 since deposited on 02 Apr 2013
8 in the past twelve months

Full-text downloads displays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.

ID Code: 58830
Item Type: Chapter in Book, Report or Conference volume (Conference contribution)
ORCID iD:
Bruns, Axelorcid.org/0000-0002-3943-133X
Measurements or Duration: 4 pages
Keywords: Big Data, Crisis Communication, Location, Twitter
DOI: 10.2991/icibet.2013.248
ISBN: 978-90-78677-57-4
Pure ID: 32468710
Divisions: Past > QUT Faculties & Divisions > Creative Industries Faculty
Past > Research Centres > ARC Centre of Excellence for Creative Industries and Innovation
Past > Research Centres > Centre for Emergency & Disaster Management
Funding:
Copyright Owner: Consult author(s) regarding copyright matters
Copyright Statement: This work is covered by copyright. Unless the document is being made available under a Creative Commons Licence, you must assume that re-use is limited to personal use and that permission from the copyright owner must be obtained for all other uses. If the document is available under a Creative Commons License (or other specified license) then refer to the Licence for details of permitted re-use. It is a condition of access that users recognise and abide by the legal requirements associated with these rights. If you believe that this work infringes copyright please provide details by email to qut.copyright@qut.edu.au
Deposited On: 02 Apr 2013 07:05
Last Modified: 03 Mar 2024 00:33