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Author Zahra Ashktorab; Christopher Brown; Manojit Nandi; Aron Culotta
Title Tweedr: Mining twitter to inform disaster response Type Conference Article
Year 2014 Publication ISCRAM 2014 Conference Proceedings – 11th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal ISCRAM 2014
Volume Issue Pages 354-358
Keywords Data mining; Disaster prevention; Disasters; Extraction; Filtration; Information systems; Social networking (online); Classification methods; Disaster response; Extraction phase; Logistic regressions; Natural disasters; Social media; Specific information; Text mining; Emergency services
Abstract In this paper, we introduce Tweedr, a Twitter-mining tool that extracts actionable information for disaster relief workers during natural disasters. The Tweedr pipeline consists of three main parts: classification, clustering and extraction. In the classification phase, we use a variety of classification methods (sLDA, SVM, and logistic regression) to identify tweets reporting damage or casualties. In the clustering phase, we use filters to merge tweets that are similar to one another; and finally, in the extraction phase, we extract tokens and phrases that report specific information about different classes of infrastructure damage, damage types, and casualties. We empirically validate our approach with tweets collected from 12 different crises in the United States since 2006.
Address University of Maryland, College Park, United States; University of Texas, Austin, United States; Carnegie Mellon University, United States; Illinois Institute of Technology, United States
Corporate Author Thesis
Publisher The Pennsylvania State University Place of Publication University Park, PA Editor S.R. Hiltz, M.S. Pfaff, L. Plotnick, and P.C. Shih.
Language English Summary Language English Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2411-3387 ISBN 9780692211946 Medium
Track Humanitarian Information Systems Expedition Conference 11th International ISCRAM Conference on Information Systems for Crisis Response and Management
Notes Approved no
Call Number Serial 275
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Author Eli Rohn; Gil Erez
Title Fighting agro-terrorism in cyberspace: A framework for intention detection using overt electronic data sources Type Conference Article
Year 2012 Publication ISCRAM 2012 Conference Proceedings – 9th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal ISCRAM 2012
Volume Issue Pages
Keywords Bioterrorism; Chemical detection; Data mining; Information retrieval; Information systems; Risk assessment; World Wide Web; Authorship; Cyber-terrorism; Digital shadow; Intelligence; Text mining; Terrorism
Abstract Agro Terrorism is “a hostile attack, towards an agricultural environment, including infrastructures and processes, in order to significantly damage national and international political interests”. This special session within the early warning track is aimed at reducing agro-terrorism related risks by either means of prevention (intelligence gathering using data mining and chatter mining, for example) or means to response to such an attack by early detection of exotic/foreign pathogenic agents, early prediction of disease dispersion patterns, implementation of biosecurity measures, and the development of future methodologies and techniques related to food defense and post-event response. This paper focuses on intention detection using overt data sources on the World Wide Web as they relate to agro-terrorism threats. The paper focuses on early detection that can lead to prevention of such acts, yet a variety of the techniques presented here are also useful for helping in post-event perpetrators detection. © 2012 ISCRAM.
Address Software and Information Systems Engineering Department, Ben Gurion University, Israel; Counter Agro Terrorism Research Center, Israel
Corporate Author Thesis
Publisher Simon Fraser University Place of Publication Vancouver, BC Editor L. Rothkrantz, J. Ristvej, Z.Franco
Language English Summary Language English Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2411-3387 ISBN 9780864913326 Medium
Track Planning and Foresight Expedition Conference 9th International ISCRAM Conference on Information Systems for Crisis Response and Management
Notes Approved no
Call Number Serial 196
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Author Andrea Zielinski; Stuart E. Middleton; Laurissa N. Tokarchuk; Xinyue Wang
Title Social media text mining and network analysis for decision support in natural crisis management Type Conference Article
Year 2013 Publication ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal ISCRAM 2013
Volume Issue Pages 840-845
Keywords Arts computing; Decision support systems; Information systems; Software prototyping; Decision supports; Link analysis; Social media; Text mining; Vgi; Web Mining; Data mining
Abstract A core issue in crisis management is to extract from the mass of incoming information what is important for situational awareness during mass emergencies. Based on a case study we develop a prototypical application, TweetComp1, which is integrated into the decision-support component of a Tsunami early warning system and demonstrates the applicability of our approach. This paper describes four novel approaches using focused twitter crawling, trustworthiness analysis, geo-parsing, and multilingual tweet classification in the context of how they could be used for monitoring crises. The validity of our state-of-the art text mining and network analysis technologies will be verified in different experiments based on a human annotated gold standard corpus.
Address Fraunhofer Institute of Optronics, System Technologies and Image Exploitation, Karlsruhe, Germany; IT Innovation Centre, University of Southampton, Southampton, United Kingdom; School of Electronic Engineering and Computer Science, Queen Mary University of London, London, United Kingdom
Corporate Author Thesis
Publisher Karlsruher Institut fur Technologie Place of Publication KIT; Baden-Baden Editor T. Comes, F. Fiedrich, S. Fortier, J. Geldermann and T. Müller
Language English Summary Language English Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2411-3387 ISBN 9783923704804 Medium
Track Social Media Expedition Conference 10th International ISCRAM Conference on Information Systems for Crisis Response and Management
Notes Approved no
Call Number Serial 1160
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