This paper presents DisBot, the first Portuguese speaking chatbot that uses social media retrieved knowledge to support citizens and first-responders in disaster scenarios, in order to improve community resilience and decision-making. It was developed and tested using Design Science Research Methodology (DSRM), being progressively matured with field specialists through several design and development iterations. DisBot uses a state-of-the-art Dual Intent Entity Transformer (DIET) architecture to classify user intents, and makes use of several dialogue policies for managing user conversations, as well as storing relevant information to be used in further dialogue turns. To generate responses, it uses real-world safety knowledge, and infers a dynamic knowledge graph that is dynamically updated in real-time by a disaster-related knowledge extraction tool, presented in previous works. Through its development iterations, DisBot has been validated by field specialists, who have considered it to be a valuable asset in disaster management.

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Disaster management,Community resilience,Situational awareness,Natural language processing,Chatbots,Knowledge graphs

• Ciências da Computação e da Informação - Ciências Naturais