Enhancing Trustworthiness and Minimising Bias Issues in Leveraging Social Media Data for Disaster Management Response
Samia Abid, Bhupesh Kumar Mishra, Dhavalkumar Thakker, Nishikant, Mishra

TL;DR
This paper explores methods to improve trustworthiness and reduce biases in social media data to enhance the effectiveness and reliability of disaster management responses using real-time information.
Contribution
It proposes a framework for identifying and mitigating biases and misinformation in social media data to support scalable disaster response systems.
Findings
Identified key factors influencing trustworthiness in social media data.
Developed techniques to detect and minimize biases and misinformation.
Demonstrated improved accuracy in disaster severity assessment.
Abstract
Disaster events often unfold rapidly, necessitating a swift and effective response. Developing action plans, resource allocation, and resolution of help requests in disaster scenarios is time-consuming and complex since disaster-relevant information is often uncertain. Leveraging real-time data can significantly deal with data uncertainty and enhance disaster response efforts. To deal with real-time data uncertainty, social media appeared as an alternative effective source of real-time data as there has been extensive use of social media during and after the disasters. However, it also brings forth challenges regarding trustworthiness and bias in these data. To fully leverage social media data for disaster management, it becomes crucial to mitigate biases that may arise due to specific disaster types or regional contexts. Additionally, the presence of misinformation within social media…
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Taxonomy
TopicsPublic Relations and Crisis Communication · Disaster Management and Resilience · Misinformation and Its Impacts
