Abstract
Currently, using the internet as a means of gathering tourism information has become standard practice. Traditionally, information related to travel was obtained from travel magazines, television, and travel agencies. However, with the widespread adoption of the internet, these sources have been largely replaced by online earches for tourism information. Additionally, visitors to tourist destinations often share their experiences on platforms like SNS (social networking services). To increase tourism, it has become essential to analyze online information. In this study, we collect regional information from the vast amount of data available on the web for use in tourism
promotion and regional revitalization. However, the data posted on SNS varies widely, and it often includes content that differs from the intended purpose of analysis. Therefore, in this study, we focus on the frequency of posts by the same user ID to classify the collected data. We examine whether it is possible to identify valuable posts through this classification based on posting frequency.
