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dc.contributor.author | Celardo, Luigi | es_ES |
dc.contributor.author | Misuraca, Michelangelo | es_ES |
dc.contributor.author | Spano, Maria | es_ES |
dc.date.accessioned | 2024-01-11T12:59:13Z | |
dc.date.available | 2024-01-11T12:59:13Z | |
dc.date.issued | 2023-09-22 | |
dc.identifier.isbn | 9788413960869 | |
dc.identifier.uri | http://hdl.handle.net/10251/201799 | |
dc.description.abstract | [EN] Tourists are increasingly involved in co-creating attractions’ symbolic images, sharing their experiences and opinions on websites like TripAdvisor and other similar rating and review platforms. In this paper, we propose a strategy for analyzing people’ opinions about tourist points of interest, using an Ambient Geographic Information approach to georeference the polarity scores of reviews. Visualizing these scores on a map can be used to obtain helpful information for implementing strategic actions and policies of institutional and business actors involved in the tourist industry, as well as to help users plan their future experiences. A case study concerning the reviews of the restaurants in Naples (Italy) shows the effectiveness of the proposal. | es_ES |
dc.format.extent | 8 | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | Editorial Universitat Politècnica de València | es_ES |
dc.relation.ispartof | 5th International Conference on Advanced Research Methods and Analytics (CARMA 2023) | |
dc.rights | Reconocimiento - No comercial - Compartir igual (by-nc-sa) | es_ES |
dc.subject | Social media | es_ES |
dc.subject | Polarity score | es_ES |
dc.subject | Georeferenced sentiment | es_ES |
dc.title | Georeferencing sentiment scores to map and explore tourist points of interest | es_ES |
dc.type | Capítulo de libro | es_ES |
dc.type | Comunicación en congreso | es_ES |
dc.identifier.doi | 10.4995/CARMA2023.2023.16429 | |
dc.rights.accessRights | Abierto | es_ES |
dc.description.bibliographicCitation | Celardo, L.; Misuraca, M.; Spano, M. (2023). Georeferencing sentiment scores to map and explore tourist points of interest. Editorial Universitat Politècnica de València. 115-122. https://doi.org/10.4995/CARMA2023.2023.16429 | es_ES |
dc.description.accrualMethod | OCS | es_ES |
dc.relation.conferencename | CARMA 2023 - 5th International Conference on Advanced Research Methods and Analytics | es_ES |
dc.relation.conferencedate | Junio 28-30, 2023 | es_ES |
dc.relation.conferenceplace | Sevilla, España | es_ES |
dc.relation.publisherversion | http://ocs.editorial.upv.es/index.php/CARMA/CARMA2023/paper/view/16429 | es_ES |
dc.description.upvformatpinicio | 115 | es_ES |
dc.description.upvformatpfin | 122 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.relation.pasarela | OCS\16429 | es_ES |