Development of a Tourist Attraction Recommendation System Using BERTopic and Color Analysis-Based Sentiment Extraction

This study aims to develop a personalized tourist destination recommendation system by analyzing the color and emotional factors of destination images. It evaluated and analyzed the emotional responses and color characteristics conveyed by images of natural resorts and urban tourist sites. A survey was conducted to collect users' emotional responses to these images, and a BERTopic model based on BERT was used to analyze text data from social media. The survey results provided a clear understanding of how users react to specific colors and emotional factors. For natural resorts, Green(G) was the most associated color, followed by Green-Yellow(GY) and Blue(B). In the case of urban tourist sites, Yellow-Red(YR) and Yellow(Y) were most commonly associated, followed by Blue-Green(BG) and Blue(B). Additionally, during the system's execution, the Bhattacharyya distance was used to measure color similarity between images, displaying images that match the user's emotions. Therefore, this study developed a recommendation system that considers the impact of destination images on users' emotions, proposing a new approach to better reflect users' emotional needs.