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Andrea Kavanaugh; Steven D. Sheetz; Riham Hassan; Seungwon Yang; Hicham G. Elmongui; Edward A. Fox; Mohamed Magdy; Donald J. Shoemaker |
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Title  |
Between a rock and a cell phone: Communication and information technology use during the 2011 Egyptian uprising |
Type |
Conference Article |
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Year |
2012 |
Publication |
ISCRAM 2012 Conference Proceedings – 9th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
ISCRAM 2012 |
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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) |
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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. |
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Address |
Virginia Tech, Blacksburg, VA 24061, United States; Arab Academy for Science and Technology, Cairo, Egypt; Alexandria University, Alexandria, Egypt |
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Publisher |
Simon Fraser University |
Place of Publication |
Vancouver, BC |
Editor |
L. Rothkrantz, J. Ristvej, Z.Franco |
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Language |
English |
Summary Language |
English |
Original Title |
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ISSN |
2411-3387 |
ISBN |
9780864913326 |
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Track |
Social Media and Collaborative Systems |
Expedition |
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Conference |
9th International ISCRAM Conference on Information Systems for Crisis Response and Management |
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Notes |
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Approved |
no |
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Call Number |
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Serial |
138 |
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Author |
Dipak Singh; Shayan Shams; Joohyun Kim; Seung-jong Park; Seungwon Yang |
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Title |
Fighting for Information Credibility: AnEnd-to-End Framework to Identify FakeNews during Natural Disasters |
Type |
Conference Article |
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Year |
2020 |
Publication |
ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
Iscram 2020 |
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Pages |
90-99 |
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Keywords |
Neural Networks, Social Network, Natural Disaster, Fake News, Deep Learning. |
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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. |
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Address |
Louisiana State University; University of Texas; Louisiana State University; Louisiana State University;Louisiana State University |
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Publisher |
Virginia Tech |
Place of Publication |
Blacksburg, VA (USA) |
Editor |
Amanda Hughes; Fiona McNeill; Christopher W. Zobel |
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Language |
English |
Summary Language |
English |
Original Title |
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Edition |
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ISSN |
978-1-949373-27-9 |
ISBN |
2411-3395 |
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Track |
AI Systems for Crisis and Risks |
Expedition |
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Conference |
17th International Conference on Information Systems for Crisis Response and Management |
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Notes |
dsingh8@lsu.edu |
Approved |
no |
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Call Number |
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Serial |
2210 |
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Author |
Steven Sheetz; Andrea Kavanaugh; Edward Fox; Riham Hassan; Seungwon Yang; Mohamed Magdy; Shoemaker Donald |
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Title |
Information Uses and Gratifications Related to Crisis: Student Perceptions since the Egyptian Uprising |
Type |
Conference Article |
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Year |
2019 |
Publication |
Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management |
Abbreviated Journal |
Iscram 2019 |
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Keywords |
Uses and gratifications theory; information sources; Internet; social media; structural equation modeling |
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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. |
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Address |
Virginia Tech, United States of America;Microsoft;Louisiana State University;Arab Academy of Science and Technology |
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Publisher |
Iscram |
Place of Publication |
Valencia, Spain |
Editor |
Franco, Z.; González, J.J.; Canós, J.H. |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Volume |
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Edition |
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ISSN |
2411-3387 |
ISBN |
978-84-09-10498-7 |
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Track |
T8- Social Media in Crises and Conflicts |
Expedition |
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Conference |
16th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2019) |
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Notes |
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Approved |
no |
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Call Number |
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Serial |
1862 |
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Author |
Seungwon Yang; Haeyong Chung; Xiao Lin; Sunshin Lee; Liangzhe Chen; Andrew Wood; Andrea Kavanaugh; Steven D. Sheetz; Donald J. Shoemaker; Edward A. Fox |
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Title |
PhaseVis1: What, when, where, and who in visualizing the four phases of emergency management through the lens of social media |
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Conference Article |
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Year |
2013 |
Publication |
ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management |
Abbreviated Journal |
ISCRAM 2013 |
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Issue |
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Pages |
912-917 |
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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 |
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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. |
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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 |
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Publisher |
Karlsruher Institut fur Technologie |
Place of Publication |
KIT; Baden-Baden |
Editor |
T. Comes, F. Fiedrich, S. Fortier, J. Geldermann and T. Müller |
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Language |
English |
Summary Language |
English |
Original Title |
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Series Editor |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2411-3387 |
ISBN |
9783923704804 |
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Track |
Social Media |
Expedition |
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Conference |
10th International ISCRAM Conference on Information Systems for Crisis Response and Management |
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Notes |
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Approved |
no |
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Call Number |
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Serial |
1122 |
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