InSight Special Lecture (30) By Dr. H Raghav Rao, University Of Texas
InSight Special Lecture (30) on “Crowd-sourced Crisis Mapping”by Dr. H Raghav Rao, AT&T Chair Professor, University of Texas at San Antonio
Date: Wednesday, August 10, 2016 | 4:30 pm
Venue: Athena Auditorium, MYRA School of Business
About the Speaker: Professor Raghav Rao is a US-based scholar of Information Systems Management. His research interests are in decision support systems, e-business, cyber-security, emergency response systems and information assurance. His recent research has implications for political revolutions, anti-terrorism initiatives, and communications during natural disasters, and corporate decision making. Professor Rao co-edited four books and has authored or co-authored more than 175 technical papers, of which more than 100 are published in archival journals and his work has received best paper and best paper runner-up awards at recent AMCIS and ICIS conferences. He is a co-editor in chief of Information Systems Frontiers, senior editor of MIS Quarterly, advisory editor of Decision Support Systems, and Associate Editor of ACM Transactions on MIS. He is also a member of the National Academy of Medicine Standing Committee on Medical and Public Health Research During Large-Scale Emergency Events. Currently, Professor Rao teaches courses in Information Assurance, Networks, and e-Commerce and has received the University Lilly Teaching Fellowship. He has also held visiting faculty appointments at Indiana University, USA; York University, Canada; Amrita University, India; and Sogang University, South Korea.
Talk Summary: Crowd-sourced crisis mapping is a phenomenon of collectivity, which allows a crowd of online volunteers to process crisis information collected from citizens for the purposes of guiding the relief efforts of crisis responders. The crowd of online volunteers generally spends more than 30% time in information categorization of crisis messages. Information categorization allows crowd of online volunteers to extract meaning from citizen-reported messages, sort crisis message by prevalence and filter citizen requests by needs. Prior literature has shown that more than 50% of the crisis messages were erroneously categorized by the crowd of online volunteers, thereby failing to convey the main idea of the citizens’ messages.
In this paper, we investigate the issue of crowd-sourced information categorization quality. We analyze the drivers of information categorization quality in the context of Haiti Earthquake. We identify the facets of “citizens’ perceptual cues” and “crowds’ social interaction” as the antecedents of information categorization quality within the Ushahidi crisis microblog . Ushahidi was used to aggregate and map citizen-reported crisis. Ushahidi also enabled crowd of online volunteers to process the citizen messages into structured reports that helped in organizing relief workers by providing them real-time data regarding citizens’ needs.
The contributions of this study are threefold. First, this study analyzes an under addressed area of collective behavior. Study of such phenomenon has become possible due to the advent of microblogs. Second, this study shows that the concept of duality of perceptual cues and social interaction as drivers of information categorization quality. Few studies have explored the quality aspect of information categorization in Ushahidi. Third, we extend the literature on collective action to the human-machine participatory interface of Ushahidi. Based on an analysis of 1477 crisis reports in the Ushahidi for the 2010 Haiti Earthquake, we provide guidelines to crisis response practitioners for crowd-sourced information categorization.
You are cordially invited.
Dr. Shalini Urs, Chairperson, MYRA School of Business