Unveiling Touristic Pulse: Harnessing Social Sensing for Dynamic Insights

This paper explores the use of social sensing to analyze tourism dynamics in Torrevieja (Alicante), a tourist coastal city in Spain. By leveraging advancements in Natural Language Processing (NLP) and Deep Learning (DL), this study classifies Twitter data into ten thematic areas outlined in Torrevieja’s Tourism Development Strategy. We aim to develop a tourism-social barometer that allows real-time monitoring of significant issues impacting tourist cities, as identified through user-generated content. This analysis provides in-depth and real-time insights into public perceptions of Torrevieja as a tourist destination, factors affecting visitor experiences, and subsequent implications for destination management and marketing strategies. Employing an interdisciplinary approach that integrates tourism studies, social media analytics, and data science, our findings reveal critical themes and patterns emerging from the social media discourse. These insights enhance understanding of local tourism dynamics and also inform broader destination management practices.