مطالعه تصویرآنلاین مقصدگردشگری شهر خلاق رشت با رویکرد متن‌کاوی

Introduction:The tourism destination image is a mental concept formed through the process of processing a large set of diverse informational sources, including beliefs, ideas, perceptions, and individual or group thoughts about a specific place, which develop over time. This is a crucial prelude to tourists' behavioral intentions toward a destination. In this regard, one of the important aspects of destination management is planning and developing its image, and conveying a desirable and positive image of the destination is of great significance. In recent years, with the development of internet technology, destination images have been created based on user-generated content about tourist destinations shared on social media platforms. This type of content operates beyond the efforts of destination marketing organizations. Therefore, valuable insights can be gained by focusing on various aspects of user behavior.
Methodology: This research has a descriptive-analytical nature and is applied to its objective. In the first step of this study, data collection was conducted. Data collection was performed using two methods. In the first method, a systematic approach was employed, utilizing a web crawler programmed in the Python software, to collect data from Twitter. In the second method, without a systematic approach, textual data was collected manually by a human user from the user comments sections of the websites "Google Maps" and "TripAdvisor" regarding the city of Rasht. In the next step, preprocessing of the collected textual data was performed. After preprocessing and normalizing the textual data, they were prepared for the data mining process. Subsequently, data clustering was conducted using the unsupervised "K-means" algorithm. In this technique, using the elbow and silhouette evaluation methods, the optimal value for K was determined to be 3.
Results: Based on the studies conducted in this research, the most important features shaping the tourism destination image-friendly and creative city of Rasht are grouped into three main clusters.Cluster 1 is the most significant and has received the most attention. Based on the most frequently mentioned words, this cluster is categorized into two subgroups: food and cuisine, and parks and gardens. Urban parks and gardens in Rasht, as unique environmental attractions, have been highly regarded by users and are viewed very positively. This potential can be leveraged to develop and enhance the city’s brand. The next most frequently mentioned cluster, Cluster 2, revolves around infrastructure, amenities, accommodation, and hotels. Hotel facilities, staff, and service quality are among the aspects frequently discussed by tourists on social media and the internet as key features of Rasht. However, accommodation and hotel services have received the highest number of negative reviews, indicating weaknesses in this area. To establish a standout image of Rasht as a destination, efforts must be made to improve infrastructure and public services, with a focus on accommodation and hospitality services. Cluster 3 ranks last in prominence. In this cluster, the Rasht Bazaar stands out as a key feature of the city’s image. It is described as a traditional market offering fresh and local products unique to the region. Another highlighted feature is the Municipality Square Complex, which has gained attention in online discussions about Rasht. The architectural style of the Municipality Square, the cultural pedestrian area extending to Sabzeh Meydan, and the proximity of the bazaar to the Municipality Square serve as major identity symbols of Rasht. These areas, characterized by their historical, cultural, and unique architectural features, attract diverse groups of visitors. The vibrant nightlife in the Municipality Square Complex is another notable aspect of its appeal, as perceived by social media users. Additionally, urban parks and gardens in Rasht are prominent in its online image. These open public spaces, enhanced by the city’s moderate climate, natural landscapes, and scenic views, offer unique experiences for tourists. Increasing the number of protected natural habitats within Rasht could serve as a potential strategy to enhance the city’s creative tourism development.
Discussion: The image of a destination results from an evaluative process that is both objective and subjective. It is formed when tourists interact with and experience the destination’s urban environment after arriving. Since altering an established image is challenging, the destination image becomes a crucial and influential factor in shaping tourists' behavioral intentions toward the destination. Essentially, the destination image serves as an initial input for tourists, encompassing a range of diverse elements. Therefore, the image of a destination should reflect its positive, unique, and distinctive features while avoiding exaggeration beyond the destination's actual capacity and potential. Overpromising can lead to negative experiences for tourists upon arrival, ultimately resulting in a poor image. Thus, planning and managing the destination image of the creative city of Rasht should aim to maintain and enhance its positive and appealing features while addressing and resolving existing shortcomings. Based on the findings of this research, the destination image of Rasht in the digital space is shaped by its unique attractions, as well as its cultural, local, and identity-based features. The city's food culture, as an intangible heritage, plays a central role in this context. The destination image of Rasht, as presented online, aligns with its global branding as a UNESCO Creative City of Gastronomy. The emphasis on food, cuisine, and the Rasht Bazaar—primarily associated with the produce and fish markets—underscores this alignment. Overall, the results of this study indicate a relatively positive image of Rasht as a creative city for tourism. In addition to examining the structure of Rasht’s destination image as a case study, this research proposes a methodological framework for analyzing big data from social media related to urban tourism.