Scenic area attractiveness in Dali City and its influencing factors evaluated using multi-source spatiotemporal data.
Scenic area attractiveness is a core factor in urban tourism development. Developments in social media and multi-source spatiotemporal data provide a basis for studying complex tourist behaviors, overcoming the limitations of traditional interview survey data. This study combines point of interest (...
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Public Library of Science (PLoS)
2025-01-01
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| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0323310 |
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| author | Di Wang Haizhong Qian |
| author_facet | Di Wang Haizhong Qian |
| author_sort | Di Wang |
| collection | DOAJ |
| description | Scenic area attractiveness is a core factor in urban tourism development. Developments in social media and multi-source spatiotemporal data provide a basis for studying complex tourist behaviors, overcoming the limitations of traditional interview survey data. This study combines point of interest (POI), mobile signaling, and microblog check-in data to analyze scenic area popularity in Dali using kernel density analysis, hotspot analysis, and gravity models. It also uses ROST-CM6 to perform sentiment analysis on microblog check-in and text data to obtain tourist satisfaction, and combines the popularity and satisfaction to assess scenic area attractiveness. Additionally, GeoDetector is used to examine the impact of subjective human factors, objective factors of the attractions themselves, and the number of POI facilities around the attractions on the scenic area attractiveness in Dali. We obtained several key findings. First, the distribution of scenic areas in Dali City showed a two-center, multi-point pattern, including two core scenic areas (i.e., Dali Ancient City and Xizhou Ancient Town) and numerous scattered areas. Second, the majority of scenic areas in Dali City were more active in the daytime than at night, whereas Dali Ancient City was most active at night. Tourists in Dali City mostly came from Yunnan Province, neighboring provinces, and economically developed coastal regions. Third, a text-based sentiment analysis revealed numerous high-frequency adjectives reflecting positive sentiment, indicating high scenic area satisfaction. Fourth, the number of internal POIs had the greatest effects on scenic area popularity and attractiveness. Specifically, the more POIs, the more popular and attractive the scenic area. The interactive decision-making power of various factors was greater than the decision-making power of individual factors. These findings provide insight into the determinants of scenic area satisfaction, providing a basis for the development of urban tourism. |
| format | Article |
| id | doaj-art-b1b1a8081bdb4cce9b82c459e8cd215f |
| institution | OA Journals |
| issn | 1932-6203 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj-art-b1b1a8081bdb4cce9b82c459e8cd215f2025-08-20T01:52:33ZengPublic Library of Science (PLoS)PLoS ONE1932-62032025-01-01205e032331010.1371/journal.pone.0323310Scenic area attractiveness in Dali City and its influencing factors evaluated using multi-source spatiotemporal data.Di WangHaizhong QianScenic area attractiveness is a core factor in urban tourism development. Developments in social media and multi-source spatiotemporal data provide a basis for studying complex tourist behaviors, overcoming the limitations of traditional interview survey data. This study combines point of interest (POI), mobile signaling, and microblog check-in data to analyze scenic area popularity in Dali using kernel density analysis, hotspot analysis, and gravity models. It also uses ROST-CM6 to perform sentiment analysis on microblog check-in and text data to obtain tourist satisfaction, and combines the popularity and satisfaction to assess scenic area attractiveness. Additionally, GeoDetector is used to examine the impact of subjective human factors, objective factors of the attractions themselves, and the number of POI facilities around the attractions on the scenic area attractiveness in Dali. We obtained several key findings. First, the distribution of scenic areas in Dali City showed a two-center, multi-point pattern, including two core scenic areas (i.e., Dali Ancient City and Xizhou Ancient Town) and numerous scattered areas. Second, the majority of scenic areas in Dali City were more active in the daytime than at night, whereas Dali Ancient City was most active at night. Tourists in Dali City mostly came from Yunnan Province, neighboring provinces, and economically developed coastal regions. Third, a text-based sentiment analysis revealed numerous high-frequency adjectives reflecting positive sentiment, indicating high scenic area satisfaction. Fourth, the number of internal POIs had the greatest effects on scenic area popularity and attractiveness. Specifically, the more POIs, the more popular and attractive the scenic area. The interactive decision-making power of various factors was greater than the decision-making power of individual factors. These findings provide insight into the determinants of scenic area satisfaction, providing a basis for the development of urban tourism.https://doi.org/10.1371/journal.pone.0323310 |
| spellingShingle | Di Wang Haizhong Qian Scenic area attractiveness in Dali City and its influencing factors evaluated using multi-source spatiotemporal data. PLoS ONE |
| title | Scenic area attractiveness in Dali City and its influencing factors evaluated using multi-source spatiotemporal data. |
| title_full | Scenic area attractiveness in Dali City and its influencing factors evaluated using multi-source spatiotemporal data. |
| title_fullStr | Scenic area attractiveness in Dali City and its influencing factors evaluated using multi-source spatiotemporal data. |
| title_full_unstemmed | Scenic area attractiveness in Dali City and its influencing factors evaluated using multi-source spatiotemporal data. |
| title_short | Scenic area attractiveness in Dali City and its influencing factors evaluated using multi-source spatiotemporal data. |
| title_sort | scenic area attractiveness in dali city and its influencing factors evaluated using multi source spatiotemporal data |
| url | https://doi.org/10.1371/journal.pone.0323310 |
| work_keys_str_mv | AT diwang scenicareaattractivenessindalicityanditsinfluencingfactorsevaluatedusingmultisourcespatiotemporaldata AT haizhongqian scenicareaattractivenessindalicityanditsinfluencingfactorsevaluatedusingmultisourcespatiotemporaldata |