Twitter Early Tsunami Warning System: A Case Study in Indonesia's Natural Disaster Management

Twitter demonstrated its value as a viable substitute to traditional communication channels during the recent disasters. However, little is written about Twitter in government for an early disaster warning system. In this exploratory empirical research, we aim to address the question: How does the government use Twitter to inform the public about disaster hazards and vulnerability? Case study and tweets content analysis are conducted on Indonesia's Twitter early tsunami warning system to answer the question in the context of the three earthquakes occurred off the west coast of Sumatra during the period of 2010-2012. Data are collected from egovernment websites of agencies involved in disaster preparedness and response. This research concludes that the Twitter-based warning system demonstrated its value as a viable complement to Indonesia's InaTEWS - a comprehensive disaster information management system for governments - by informing the public and creating public value through its communication speed, reach and information quality.

[1]  Su Yean Teh,et al.  Tsunami Simulation for Capacity Development , 2011 .

[2]  V. Lakshmanan Automating the Analysis of Spatial Grids , 2012 .

[3]  Yong Lu,et al.  Information exchange in virtual communities under extreme disaster conditions , 2011, Decis. Support Syst..

[4]  Ralf Klischewski,et al.  E-Government Integration and Interoperability: Framing the Research Agenda , 2007 .

[5]  L. Palen Online Social Media in Crisis Events. , 2008 .

[6]  Hirokazu Tatano,et al.  E-Government Challenge in Disaster Evacuation Response: The Role of RFID Technology in Building Safe and Secure Local Communities , 2010, 2010 43rd Hawaii International Conference on System Sciences.

[7]  Teun Terpstra,et al.  Filling in the blanks: Constructing effective flood warning messages using the Flood Warning Communicator (FWC) , 2011, ISCRAM.

[8]  V. Lakshmanan Automating the Analysis of Spatial Grids: A Practical Guide to Data Mining Geospatial Images for Human & Environmental Applications , 2012 .

[9]  Pedro M. Reyes,et al.  RFID in the contemporary supply chain: multiple perspectives on its benefits and risks , 2008 .

[10]  Allen S. Lee A Scientific Methodology for MIS Case Studies , 1989, MIS Q..

[11]  Sean P. Goggins,et al.  Relief work after the 2010 Haiti earthquake: leadership in an online resource coordination network , 2012, CSCW '12.

[12]  Ioannis M. Dokas,et al.  Setting the Specification Framework of an Early Warning System Using IDEF0 and Information Modeling , 2008 .

[13]  Janos J. Bogardi,et al.  Early warning systems in the context of disaster risk management , 2006 .

[14]  Zhang Wei,et al.  Role Of Social Media In Knowledge Management During Natural Disaster Management , 2012 .

[15]  Shaun P. Williams,et al.  Exploring the status of tsunami early warning systems in Samoa , 2006 .

[16]  Gavin P. Hayes,et al.  The 25 October 2010 Mentawai tsunami earthquake, from real‐time discriminants, finite‐fault rupture, and tsunami excitation , 2011 .

[17]  Cecep Subarya,et al.  GPS-controlled tide gauges in Indonesia – a German contribution to Indonesia's Tsunami Early Warning System , 2011 .

[18]  John Yen,et al.  Classifying text messages for the haiti earthquake , 2011, ISCRAM.