Please use this identifier to cite or link to this item:
Title: CrisisTracker: crowdsourced social media curation for disaster awareness
Authors: Rogstadius, Jakob 
Vukovic, Maja 
Teixeira, Claudio A. 
Kostakos, Vassilis 
Karapanos, Evangelos 
Laredo, Jim Alain 
Keywords: Large-scale event;Lexical similarity;Local language;Natural disasters;Novel techniques;Relief organizations;Situation awareness;Specific information;Data mining;Social networking (online);Disasters
Category: Computer and Information Sciences
Field: Natural Sciences
Issue Date: 17-Sep-2013
Publisher: ACM
Source: IBM Journal of Research and Development, 2013, Volume 57, Issue 5, Article number 6601695
Journal: IBM Journal of Research and Development 
Abstract: Victims, volunteers, and relief organizations are increasingly using social media to report and act on large-scale events, as witnessed in the extensive coverage of the 2010-2012 Arab Spring uprisings and 2011 Japanese tsunami and nuclear disasters. Twitter® feeds consist of short messages, often in a nonstandard local language, requiring novel techniques to extract relevant situation awareness data. Existing approaches to mining social media are aimed at searching for specific information, or identifying aggregate trends, rather than providing narratives. We present CrisisTracker, an online system that in real time efficiently captures distributed situation awareness reports based on social media activity during large-scale events, such as natural disasters. CrisisTracker automatically tracks sets of keywords on Twitter and constructs stories by clustering related tweets on the basis of their lexical similarity. It integrates crowdsourcing techniques, enabling users to verify and analyze stories. We report our experiences from an 8-day CrisisTracker pilot deployment during 2012 focused on the Syrian civil war, which processed, on average, 446,000 tweets daily and reduced them to consumable stories through analytics and crowdsourcing. We discuss the effectiveness of CrisisTracker based on the usage and feedback from 48 domain experts and volunteer curators. © 1957-2012 IBM.
ISSN: 0018-8646
DOI: 10.1147/JRD.2013.2260692
Rights: © Copyright 2013 by International Business Machines Corporation.
Type: Article
Appears in Collections:Άρθρα/Articles

Show full item record


checked on Sep 14, 2019

Page view(s)

Last Week
Last month
checked on Sep 20, 2019

Google ScholarTM



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.