Participation Patterns and Reliability of Human Sensing in Crowd-Sourced Disaster Management
RIS ID
116305
Abstract
Over the last ten years, there has been a significant increase in crowd-sourcing applications for disaster management. Their success depends heavily on the behaviour of social media users, acting as human sensors during disaster monitoring and emergency response. Unlike their technological counterparts, human sensors are complex social entities, contributing in different ways to their collective task and creating varying participation patterns through social media. Failing to understand these participation patterns limits our capacity to evaluate the reliability of human sensing in different contexts. Based on an analysis of flood-related information contributed by Twitter users in Jakarta during the 2014/2015 and 2015/2016 monsoonal seasons, this study establishes four categories of human sensors and their respective levels of reliability for disaster management. The results have significant implications for how we frame expectations and develop reliance on the use of social media for disaster management. Importantly, the results will serve as a useful guide for understanding levels of incentive that may be required to motivate members of the different categories of social media users during emergencies and disasters.
Publication Details
Ogie, R. I., Forehead, H., Clarke, R. J. & Perez, P. (2018). Participation Patterns and Reliability of Human Sensing in Crowd-Sourced Disaster Management. Information Systems Frontiers: a journal of research and innovation, 20 (4), 713-728.