Automatic detection method of tourist spots using SNS

Abstract

Tourism information collection using the web has become popular in recent years. Moreover, tourists are increasingly using the web to obtain tourist information. Particularly because of the spread of social network services (SNSs), various tourism information is available. Various studies are being conducted using Twitter, which is one of SNS. A low-cost moving average method using geotagged tweets posted location information has been proposed to estimate the best time (peak period) for phenological observation. Geotagged tweets are also useful for estimating and acquiring local tourist information in real time, as a social sensor, because the information can reflect real-world situations. We have been working on, we are pursuing an estimation of the best time to view cherry blossoms. Our earlier studies have improved methods of estimating cherry blossom viewing times. The research so far can estimate the spot that the user knows. However, we cannot estimate the cherry blossoms that the users do not know. Therefore, a user requires a system that is independent of the amount of knowledge. It is possible to provide useful information to all users. We propose a prototype system that estimates the best time without prior knowledge of tourist destinations. In the early stages, the purpose is to use tweets to find spots already featured in magazines and the web. As described herein, we detected spots automatically using a geotagged tweet by visualization with a heat map and setting conditions. The proposed method achieved it in about 80%.