AI-Driven Chatbots for Emergency and Disaster Response: A Global Bibliometric Analysis
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The objective of this study is to analyze the global scientific production on the use of chatbots in emergencies and disaster response, identifying research trends, collaboration patterns, and thematic evolution. A bibliometric analysis was conducted using 97 documents indexed in Scopus between 2019 and July 2025. The analysis employed MASHA and VOSviewer to combine performance indicators with science mapping, enabling the visualization of research networks and emerging topics. Findings reveal an annual growth rate of 34.17%, encompassing 75 publication sources and 367 contributing authors, with a 100% co-authorship rate. Articles and conference papers account for 51.5% and 42.3% of the literature, with an average of 7.1 citations per document and an overall h-index of 15. The United States, China, and India lead global contributions, while keyword co-occurrence analysis indicates increasing interest in human-centered communication, coordination, and artificial intelligence applications. However, topics such as healthcare integration, crisis data management, and ethical governance remain underexplored. This study advances the field by systematizing a previously dispersed body of research, revealing the conceptual foundations and intellectual structure of chatbot applications in emergency contexts. By combining bibliometric evidence with a human-centered perspective, a comprehensive framework is introduced that assesses the ethical, social, and technological dimensions to develop resilient and reliable emergency response systems for the future.
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