Spot extraction and analysis using an automatic detection method of tourist spots using SNS. (13th December 2021)

• Record Type: Journal Article
• Authors: Takahashi, Munenori; Endo, Masaki; Ohno, Shigeyoshi; Hirota, Masaharu; Ishikawa, Hiroshi
• Is Part Of: International journal of intelligent information and database systems. Volume 15:Number 1(2022)
• Page Start: 6
• Page End: 27
• Publication Date: 2021-12-13
• Subjects: social network service -- SNS -- mining -- sightseeing -- spot detection; Database management -- Computer programs -- Periodicals; Information retrieval -- Computer programs -- Periodicals; Information storage and retrieval systems -- Computer programs -- Periodicals; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; Intelligent agents (Computer software) -- Periodicals; 006.33
• Languages: English
• ISSNs: 1751-5858

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.