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Author (up) Andrea Kavanaugh; Steven D. Sheetz; Riham Hassan; Seungwon Yang; Hicham G. Elmongui; Edward A. Fox; Mohamed Magdy; Donald J. Shoemaker
Title Between a rock and a cell phone: Communication and information technology use during the 2011 Egyptian uprising 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 Cellular telephones; Information systems; Mobile phones; Contextual factors; Information technology use; Innovation diffusion; Innovation diffusion theory; Middle East; Opinion leaders; Social media; Social media datum; Social networking (online)
Abstract Many observers heralded the use of social media during recent political uprisings in the Middle East even dubbing Iran's post election protests a “Twitter Revolution”. We seek to put into perspective the use of social media in Egypt during the mass political demonstrations in 2011. We draw on innovation diffusion theory to argue that these media could have had an impact beyond their low adoption rates due to other factors related to demographics and social networks. We supplement our social media data analysis with survey data we collected in June 2011 from an opportunity sample of Egyptian youth. We conclude that in addition to the contextual factors noted above, the individuals within Egypt who used Twitter during the uprising have the characteristics of opinion leaders. These findings contribute to knowledge regarding the role of opinion leaders and social media, especially Twitter, during violent political demonstrations. © 2012 ISCRAM.
Address Virginia Tech, Blacksburg, VA 24061, United States; Arab Academy for Science and Technology, Cairo, Egypt; Alexandria University, Alexandria, Egypt
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 Social Media and Collaborative Systems Expedition Conference 9th International ISCRAM Conference on Information Systems for Crisis Response and Management
Notes Approved no
Call Number Serial 138
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Author (up) Dipak Singh; Shayan Shams; Joohyun Kim; Seung-jong Park; Seungwon Yang
Title Fighting for Information Credibility: AnEnd-to-End Framework to Identify FakeNews during Natural Disasters Type Conference Article
Year 2020 Publication ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal Iscram 2020
Volume Issue Pages 90-99
Keywords Neural Networks, Social Network, Natural Disaster, Fake News, Deep Learning.
Abstract Fast-spreading fake news has become an epidemic in the post-truth world of politics, the stock market, or even during natural disasters. A large amount of unverified information may reach a vast audience quickly via social media. The effect of misinformation (false) and disinformation (deliberately false) is more severe during the critical time of natural disasters such as flooding, hurricanes, or earthquakes. This can lead to disruptions in rescue missions and recovery activities, costing human lives and delaying the time needed for affected communities to return to normal. In this paper, we designed a comprehensive framework which is capable of developing a training set and trains a deep learning model for detecting fake news events occurring during disasters. Our proposed framework includes infrastructure to collect Twitter posts which spread false information. In our model implementation, we utilized the Transfer Learning scheme to transfer knowledge gained from a large and general fake news dataset to relatively smaller fake news events occurring during disasters as a means of overcoming the limited size of our training dataset. Our detection model was able to achieve an accuracy of 91.47\% and F1 score of 90.89 when it was trained with the first 28 hours of Twitter data. Our vision for this study is to help emergency managers during disaster response with our framework so that they may perform their rescue and recovery actions effectively and efficiently without being distracted by false information.
Address Louisiana State University; University of Texas; Louisiana State University; Louisiana State University;Louisiana State University
Corporate Author Thesis
Publisher Virginia Tech Place of Publication Blacksburg, VA (USA) Editor Amanda Hughes; Fiona McNeill; Christopher W. Zobel
Language English Summary Language English Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 978-1-949373-27-9 ISBN 2411-3395 Medium
Track AI Systems for Crisis and Risks Expedition Conference 17th International Conference on Information Systems for Crisis Response and Management
Notes dsingh8@lsu.edu Approved no
Call Number Serial 2210
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Author (up) Seungwon Yang; Haeyong Chung; Xiao Lin; Sunshin Lee; Liangzhe Chen; Andrew Wood; Andrea Kavanaugh; Steven D. Sheetz; Donald J. Shoemaker; Edward A. Fox
Title PhaseVis1: What, when, where, and who in visualizing the four phases of emergency management through the lens of social media 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 912-917
Keywords Civil defense; Classification (of information); Data visualization; Information systems; Risk management; 10-fold cross-validation; Classification algorithm; Classification evaluation; Emergency management; Potential utility; ThemeRiver; Through the lens; Twitter; Disasters
Abstract The Four Phase Model of Emergency Management has been widely used in developing emergency/disaster response plans. However, the model has received criticism contrasting the clear phase distinctions in the model with the complex and overlapping nature of phases indicated by empirical evidence. To investigate how phases actually occur, we designed PhaseVis based on visualization principles, and applied it to Hurricane Isaac tweet data. We trained three classification algorithms using the four phases as categories. The 10-fold cross-validation showed that Multi-class SVM performed the best in Precision (0.8) and Naïve Bayes Multinomial performed the best in F-1 score (0.782). The tweet volume in each category was visualized as a ThemeRiver[TM], which shows the 'What' aspect. Other aspects – 'When', 'Where', and 'Who' – Are also integrated. The classification evaluation and a sample use case indicate that PhaseVis has potential utility in disasters, aiding those investigating a large disaster tweet dataset.
Address Department of Computer Science, Virginia Tech, Blacksburg, VA 24061, United States; Department of Accounting and Information Systems, Virginia Tech, Blacksburg, VA 24061, United States; Department of Sociology, Virginia Tech, Blacksburg, VA 24061, United States
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 1122
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Author (up) Steven Sheetz; Andrea Kavanaugh; Edward Fox; Riham Hassan; Seungwon Yang; Mohamed Magdy; Shoemaker Donald
Title Information Uses and Gratifications Related to Crisis: Student Perceptions since the Egyptian Uprising Type Conference Article
Year 2019 Publication Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management Abbreviated Journal Iscram 2019
Volume Issue Pages
Keywords Uses and gratifications theory; information sources; Internet; social media; structural equation modeling
Abstract People use diverse sources of information, e.g., newspapers, TV, Internet news, social media, and face-to-face

conversations, to make sense of crises. We apply uses and gratifications theory (UGT) and structural equation

modeling to illustrate how using internet-based information sources since the political uprisings in Egypt influence

perceptions of information satisfaction. Consistent with expectations we find that content and process gratifications

constructs combine to explain information satisfaction, while social gratifications do not significantly influence

satisfaction in the context of a crisis. This suggests that UGT is useful for evaluating the use of information

technology in a context where information is limited in quantity and reliability.
Address Virginia Tech, United States of America;Microsoft;Louisiana State University;Arab Academy of Science and Technology
Corporate Author Thesis
Publisher Iscram Place of Publication Valencia, Spain Editor Franco, Z.; González, J.J.; Canós, J.H.
Language English Summary Language English Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 2411-3387 ISBN 978-84-09-10498-7 Medium
Track T8- Social Media in Crises and Conflicts Expedition Conference 16th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2019)
Notes Approved no
Call Number Serial 1862
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