Title | Understanding destination brand love using machine learning and content analysis method |
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Type | Journal article |
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Authors | Seyyedamiri, N., Pour, A.H., Zaeri, E. and Nazarian, A. |
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Abstract | This study aims to apply the concept of brand love in tourist destinations in order to identify the core-elements that could have influential impacts on generating destination brand love. This has been carried out by using a mixed-method of machine learning and content analysis. We have discovered that the topics have been generated for historical landmarks and destinations by analyzing the visitors’ on-line reviews are architecture, historical sites, tradition and shrine places, which could be similar to other tourist historical destinations in different part of the world. However, this study has the potential to be a model for other researches related to different destinations with possible different topics emerged. Our study contributes by providing both researchers and managers a novel method to understand what attributes of destination brand love they need to posit more emphasize to attract more visitors based on the destination type. |
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Keywords | Tourism, Leisure and Hospitality Management |
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| Geography, Planning and Development |
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Journal | Current Issues in Tourism |
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Journal citation | 25 (9), pp. 1451-1466 |
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ISSN | 1368-3500 |
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| 1747-7603 |
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Year | 2022 |
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Publisher | Taylor & Francis |
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Accepted author manuscript | File Access Level Open (open metadata and files) |
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Digital Object Identifier (DOI) | https://doi.org/10.1080/13683500.2021.1924634 |
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Web address (URL) | https://doi.org/10.1080/13683500.2021.1924634 |
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Publication dates |
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Published online | 18 May 2021 |
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Published in print | 2022 |
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Page range | 1-16 |
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