AI-Driven Social Media Analysis for Disaster Situational Awareness in Smart Urban Environments

AI-Driven Social Media Analysis for Disaster Situational Awareness in Smart Urban Environments

Ravinder Singh (SR University, India), Geetha Manoharan (SR University, India), Samrath Singh (Vellore Institute of Technology, Chennai, India), and Simranjot Singh (Delhi University, India)
Copyright: © 2025 |Pages: 30
DOI: 10.4018/979-8-3693-7832-8.ch007
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Abstract

This paper explores the transformative impact of social media analytics in disaster response. By utilizing advanced algorithms and machine learning, social media analytics enables the rapid processing of vast data streams, delivering real-time insights and trends crucial for effective disaster management. The paper highlights how social media has evolved into a vital tool for crisis communication, geolocation-based disaster response, and sentiment analysis, offering valuable insights into the emotional and psychological effects of disasters. It addresses the challenges of integrating AI in this realm, emphasizing the necessity of data privacy, ethical considerations, and transparent public engagement. The paper shows both the huge potential and inherent difficulties of using AI-driven social media analysis in disaster management by looking at a wide range of real-life case studies and opportunities within smart urban environments.
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