Title: Spot extraction and analysis using an automatic detection method of tourist spots using SNS

Authors: Munenori Takahashi; Masaki Endo; Shigeyoshi Ohno; Masaharu Hirota; Hiroshi Ishikawa

Addresses: Polytechnic University, Kodaira-shi, Tokyo, Japan ' Division of Core Manufacturing, Polytechnic University, Kodaira-shi, Tokyo, Japan ' Division of Core Manufacturing, Polytechnic University, Kodaira-shi, Tokyo, Japan ' Faculty of Informatics, Okayama University of Science, Okayama-shi, Okayama, Japan ' Graduate School of System Design, Tokyo Metropolitan University, Hino-shi Tokyo, Japan

Abstract: Tourism information collection using the social network services (SNSs) has become popular in recent years. Geotagged tweets are useful as a social sensor for estimating and acquiring local tourist information in real time because the information can reflect real-world situations. Earlier studies of methods of estimating cherry blossom viewing times have typically relied on the assumption that one knows a tourist destination: it is impossible to estimate cherry blossom tourist spots that a system user does not know. In its early stages, it can use tweets to find spots already featured in magazines and on the internet. As described herein, spots were detected automatically using a geotagged tweet by visualisation with a heat map and by setting conditions. The proposed method achieved it in about 80% of cases. We also used geotagged Tweets to assess observations of cherry blossom 'front lines' of viewing.

Keywords: social network service; SNS; mining; sightseeing; spot detection.

DOI: 10.1504/IJIIDS.2022.120144

International Journal of Intelligent Information and Database Systems, 2022 Vol.15 No.1, pp.6 - 27

Received: 04 Nov 2020
Accepted: 10 Jun 2021
Published online: 07 Jan 2022 *