Advancing smart tourism destinations: A case study using bidirectional encoder representations from transformers‐based occupancy predictions in torrevieja (Spain)
Abstract Tourism represents a crucial socio‐economic pillar globally, yet the multifaceted challenges it poses necessitate innovative management approaches. The paradigm of smart tourism harnesses advanced data analytics tools to promote both profitability and sustainability in tourist destinations,...
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| Format: | Article |
| Language: | English |
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Wiley
2024-12-01
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| Series: | IET Smart Cities |
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| Online Access: | https://doi.org/10.1049/smc2.12085 |
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| author | José Ginés Giménez Manuel José Giner Pérez de Lucia Marco Antonio Celdrán Bernabeu José Norberto Mazón López Juan Carlos Cano Escribá José María Cecilia Canales |
| author_facet | José Ginés Giménez Manuel José Giner Pérez de Lucia Marco Antonio Celdrán Bernabeu José Norberto Mazón López Juan Carlos Cano Escribá José María Cecilia Canales |
| author_sort | José Ginés Giménez Manuel |
| collection | DOAJ |
| description | Abstract Tourism represents a crucial socio‐economic pillar globally, yet the multifaceted challenges it poses necessitate innovative management approaches. The paradigm of smart tourism harnesses advanced data analytics tools to promote both profitability and sustainability in tourist destinations, leading to new levels of destination smartness. Accurate tourist occupancy prediction, particularly in areas dominated by second‐home accommodations where traditional hospitality data may be insufficient, plays a key role in optimising tourism management. To address this data gap, our prior research employed ARIMA modelling on Airbnb booking time series and analysed tourism‐related Twitter conversations to forecast occupancy levels in Torrevieja (Alicante); a prominent second‐home tourism destination in Southeastern Spain. In this extended study, we delve deeper into the realm of social sensing by utilising bidirectional encoder representations from transformers (BERT) for topic modelling. Our methodology involves the processing and analysis of Twitter data to identify prominent themes related to Torrevieja. The findings not only reveal nuanced perceptions and discussions about the destination but also underscore the effectiveness of BERT in capturing intricate topic dynamics. Importantly, this work highlights how the alignment of specific topics with booking patterns can further enhance predictive accuracy for tourist occupancy, presenting a robust toolkit for stakeholders in the tourism sector. |
| format | Article |
| id | doaj-art-fec39b63f4e24c2f804b4cc277577448 |
| institution | DOAJ |
| issn | 2631-7680 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Smart Cities |
| spelling | doaj-art-fec39b63f4e24c2f804b4cc2775774482025-08-20T02:40:32ZengWileyIET Smart Cities2631-76802024-12-016442244010.1049/smc2.12085Advancing smart tourism destinations: A case study using bidirectional encoder representations from transformers‐based occupancy predictions in torrevieja (Spain)José Ginés Giménez Manuel0José Giner Pérez de Lucia1Marco Antonio Celdrán Bernabeu2José Norberto Mazón López3Juan Carlos Cano Escribá4José María Cecilia Canales5Department of Computer Engineering (DISCA) Universitat Politècnica de València Valencia SpainDepartment of Computer Engineering (DISCA) Universitat Politècnica de València Valencia SpainUniversity Laboratory for Smart Tourism of Torrevieja University of Alicante Alicante SpainUniversity Institute of Computer Research (IUII) University of Alicante Alicante SpainDepartment of Computer Engineering (DISCA) Universitat Politècnica de València Valencia SpainDepartment of Computer Engineering (DISCA) Universitat Politècnica de València Valencia SpainAbstract Tourism represents a crucial socio‐economic pillar globally, yet the multifaceted challenges it poses necessitate innovative management approaches. The paradigm of smart tourism harnesses advanced data analytics tools to promote both profitability and sustainability in tourist destinations, leading to new levels of destination smartness. Accurate tourist occupancy prediction, particularly in areas dominated by second‐home accommodations where traditional hospitality data may be insufficient, plays a key role in optimising tourism management. To address this data gap, our prior research employed ARIMA modelling on Airbnb booking time series and analysed tourism‐related Twitter conversations to forecast occupancy levels in Torrevieja (Alicante); a prominent second‐home tourism destination in Southeastern Spain. In this extended study, we delve deeper into the realm of social sensing by utilising bidirectional encoder representations from transformers (BERT) for topic modelling. Our methodology involves the processing and analysis of Twitter data to identify prominent themes related to Torrevieja. The findings not only reveal nuanced perceptions and discussions about the destination but also underscore the effectiveness of BERT in capturing intricate topic dynamics. Importantly, this work highlights how the alignment of specific topics with booking patterns can further enhance predictive accuracy for tourist occupancy, presenting a robust toolkit for stakeholders in the tourism sector.https://doi.org/10.1049/smc2.12085artificial intelligencecity designdata analytics and machine learningdata structuresgovernanceplanning & policy |
| spellingShingle | José Ginés Giménez Manuel José Giner Pérez de Lucia Marco Antonio Celdrán Bernabeu José Norberto Mazón López Juan Carlos Cano Escribá José María Cecilia Canales Advancing smart tourism destinations: A case study using bidirectional encoder representations from transformers‐based occupancy predictions in torrevieja (Spain) IET Smart Cities artificial intelligence city design data analytics and machine learning data structures governance planning & policy |
| title | Advancing smart tourism destinations: A case study using bidirectional encoder representations from transformers‐based occupancy predictions in torrevieja (Spain) |
| title_full | Advancing smart tourism destinations: A case study using bidirectional encoder representations from transformers‐based occupancy predictions in torrevieja (Spain) |
| title_fullStr | Advancing smart tourism destinations: A case study using bidirectional encoder representations from transformers‐based occupancy predictions in torrevieja (Spain) |
| title_full_unstemmed | Advancing smart tourism destinations: A case study using bidirectional encoder representations from transformers‐based occupancy predictions in torrevieja (Spain) |
| title_short | Advancing smart tourism destinations: A case study using bidirectional encoder representations from transformers‐based occupancy predictions in torrevieja (Spain) |
| title_sort | advancing smart tourism destinations a case study using bidirectional encoder representations from transformers based occupancy predictions in torrevieja spain |
| topic | artificial intelligence city design data analytics and machine learning data structures governance planning & policy |
| url | https://doi.org/10.1049/smc2.12085 |
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