Solo Consumption – A machine learning approach
[EN] This study aims at conceptualizing the solo tourism consumption journey. We use a semisupervised machine learning approach and analyze more than 27,000 tweets. The seed sets extraction, seed and topic confidence and model fit evaluations will provide us with the dimension of solo tourism concep...
| Autores: | , , |
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| Tipo de recurso: | capítulo de libro |
| Fecha de publicación: | 2023 |
| País: | España |
| Institución: | Universitat Politècnica de València (UPV) |
| Repositorio: | RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia |
| Idioma: | inglés |
| OAI Identifier: | oai:riunet.upv.es:10251/201798 |
| Acceso en línea: | https://riunet.upv.es/handle/10251/201798 |
| Access Level: | acceso abierto |
| Palabra clave: | Solo tourism Semi-supervised Latent Dirichlet Allocation (LDA) Machine learning approach Tweets |
| Sumario: | [EN] This study aims at conceptualizing the solo tourism consumption journey. We use a semisupervised machine learning approach and analyze more than 27,000 tweets. The seed sets extraction, seed and topic confidence and model fit evaluations will provide us with the dimension of solo tourism conceptualization.The results will reveal how consumers perceive solo tourism consumption. This study provides scholars and managers with an evidencebased solo consumption conceptualization, as well as with a marketing, psychological, and operation tool to manage the solo consumer segment. |
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