A Study on Image Perception of Ice-Snow Tourism using Text Mining - Focusing on Jilin Province, China -
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초록
(Background and Purpose) The tourism destination image (TDI) play a crucial role in forming tourism decisions, as potential tourists often rely on the perceived image of the destination when choosing where to travel. To stand out in a homogenized tourism market, a unique and distinctive destination image must be established in the minds of tourists, thereby enhancing the location's irreplaceability. With the rapid development of internet technology, a wealth of authentic and reliable online data has become available. Scholars increasingly employ online text analysis methods to examine tourists' perceptions of destination images. This study aims to analyze reviews generated by tourists on online travel agencies (OTA) to understand their perception of the image of ice-snow tourism in Jilin Province. It seeks to identify the strengths and weaknesses of ice-snow tourism attractions from the tourists' perspective and provide references for promoting the sustainable development of ice-snow tourism in Jilin Province. (Method) This study utilized TF-IDF and sentiment analysis, two common text mining algorithms, to analyze online reviews of 4 representative tourist attractions in Jilin Province. These methods were used to examine tourists' cognitive and affective perceptions of ice-snow tourism in the region. Unlike traditional methods, text mining algorithms do not rely solely on word frequency to identify keywords, thus avoiding the limitations of earlier approaches. These algorithms can more accurately identify the most representative keywords and allow for a deeper exploration of underlying content, which is crucial for understanding tourist perceptions. (Results) The study found that the perceived images of Changbai Mountain Scenic Area, Changchun Ice and Snow World, Vanke Songhua Lake Resort, and Wusong Island are destinations for ice and snow sightseeing, ice and snow entertainment, ice and snow sports, and viewing ice and snow wonders, respectively. Despite these differing characteristics, they all elicited positive emotional responses from visitors, indicating general satisfaction with ice-snow tourism in Jilin Province. The regretful emotions of tourists are mainly caused by the influence of weather, which makes the expected Tianchi and rime invisible. (Conclusion) The study highlights the value of online reviews on OTAs as an unstructured data source, as they offer insights into tourists' focus and emotional attitudes towards a destination. Through text mining and analysis, the research reveals tourists' perceived images of ice-snow tourism in Jilin Province, clarifying their areas of concern and emotional attitudes. These insights provide valuable decision-making references for tourism managers and offer guidance to other destinations that can utilize this method to develop data-driven strategies to enhance and elevate their destination image.
Abstract
(Background and Purpose) The tourism destination image (TDI) play a crucial role in forming tourism decisions, as potential tourists often rely on the perceived image of the destination when choosing where to travel. To stand out in a homogenized tourism market, a unique and distinctive destination image must be established in the minds of tourists, thereby enhancing the location's irreplaceability. With the rapid development of internet technology, a wealth of authentic and reliable online data has become available. Scholars increasingly employ online text analysis methods to examine tourists' perceptions of destination images. This study aims to analyze reviews generated by tourists on online travel agencies (OTA) to understand their perception of the image of ice-snow tourism in Jilin Province. It seeks to identify the strengths and weaknesses of ice-snow tourism attractions from the tourists' perspective and provide references for promoting the sustainable development of ice-snow tourism in Jilin Province. (Method) This study utilized TF-IDF and sentiment analysis, two common text mining algorithms, to analyze online reviews of 4 representative tourist attractions in Jilin Province. These methods were used to examine tourists' cognitive and affective perceptions of ice-snow tourism in the region. Unlike traditional methods, text mining algorithms do not rely solely on word frequency to identify keywords, thus avoiding the limitations of earlier approaches. These algorithms can more accurately identify the most representative keywords and allow for a deeper exploration of underlying content, which is crucial for understanding tourist perceptions. (Results) The study found that the perceived images of Changbai Mountain Scenic Area, Changchun Ice and Snow World, Vanke Songhua Lake Resort, and Wusong Island are destinations for ice and snow sightseeing, ice and snow entertainment, ice and snow sports, and viewing ice and snow wonders, respectively. Despite these differing characteristics, they all elicited positive emotional responses from visitors, indicating general satisfaction with ice-snow tourism in Jilin Province. The regretful emotions of tourists are mainly caused by the influence of weather, which makes the expected Tianchi and rime invisible. (Conclusion) The study highlights the value of online reviews on OTAs as an unstructured data source, as they offer insights into tourists' focus and emotional attitudes towards a destination. Through text mining and analysis, the research reveals tourists' perceived images of ice-snow tourism in Jilin Province, clarifying their areas of concern and emotional attitudes. These insights provide valuable decision-making references for tourism managers and offer guidance to other destinations that can utilize this method to develop data-driven strategies to enhance and elevate their destination image.
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