A Generative AI-Driven Tourism Information Dissemination Support System with Direct Posting to SNS

Shinichi Nabeta (), Takahiro Sugiyama, Satoshi Watanabe and Hiroaki Yuze
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Shinichi Nabeta: University of Shizuoka
Takahiro Sugiyama: Shizuoka University
Satoshi Watanabe: Nihon University
Hiroaki Yuze: University of Shizuoka

A chapter in Information and Communication Technologies in Tourism 2025, 2025, pp 27-38 from Springer

Abstract: Abstract The tourism industry, having been impacted by the COVID-19 pandemic, is witnessing a growing expectation for smart tourism, which leverages advanced technologies such as Information and Communication Technology (ICT). In Japan, especially among younger generations, there is an increasing trend of gathering travel information through Social Networking Services (SNS). However, the tourism industry in Japan faces the problem of a labor shortage. To address this problem, we developed a generative AI-driven system that supports the dissemination of tourism information by converting it for direct posting to various SNS platforms. The Lake Hamana Kanzanji Onsen Tourism Association, a local tourism association in Japan, also faced difficulties in disseminating tourism information via SNS due to a lack of labor and insufficient knowledge about SNS. Therefore, this paper focuses on the development of a system specifically for the Lake Hamana Kanzanji Onsen Tourism Association. The system has undergone several improvements and now includes features such as generative AI-driven text conversion for each SNS platform, multilingual support, and direct posting functionality using Application Programming Interfaces (APIs). In this paper, we describe the background, overview, and effectiveness of the system development.

Keywords: Tourism Information Dissemination Support System; Generative AI; Social Networking Service; The Lake Hamana Kanzanji Onsen Tourism Association (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:spr:prbchp:978-3-031-83705-0_3

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DOI: 10.1007/978-3-031-83705-0_3

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