Analysis of Tourism Hotspot Behaviour Based on Geolocated Travel Blog Data: The Case of Qyer

Abstract

We contribute a system design and a generalized formal methodology to segment tourists based on their geolocated blogging behaviour according to their interests in identified tourist hotspots. Thus, it is possible to identify and target groups that are possibly interested in alternative destinations to relieve overtourism. A pilot application in a case study of Chinese travel in Switzerland by analysing Qyer travel blog data demonstrates the potential of our method. Accordingly, we contribute four conclusions supported by empirical data. First, our method can enable discovery of plausible geographical distributions of tourist hotspots, which validates the plausibility of the data and its collection. Second, our method discovered statistically significant stochastic dependencies that meaningfully differentiate the observed user base, which demonstrates its value for segmentation. Furthermore, the case study contributes two practical insights for tourism management. Third, Chinese independent travellers, which are the main target group of Qyer, are mainly interested in the discovered travel hotspots, similar to tourists on packaged tours, but also show interest in alternative places. Fourth, the proposed user segmentation revealed two clusters based on users’ social media activity level. For tourism research, users within the second cluster are of interest, which are defined by two segmentation attributes: they blogged about more than just one location, and they have followers. These tourists are significantly more likely to be interested in alternative destinations out of the hotspot axis. Knowing this can help define a target group for marketing activities to promote alternative destinations.

Chinese tourists in Nordic countries: An analysis of spatio-temporal behavior using geo-located travel blog data

“…The above shortcoming merits further empirical research and methodological evaluations. The obvious next step would be to integrate more travel data sources, such as other geo-located travel blogs from Ctrip ( Ma, Wang, Xu, & Tai, 2018 ) or Qyer ( Kaufmann et al, 2019 ), microblogs from Weibo ( Zhang et al, 2020 ) or Twitter ( Maeda, Yoshida, Toriumi, & Ohashi, 2018 ) and geo-tagged photos from Flickr ( Su, Wan, Hu, & Cai, 2016 ) or Panoramio ( Orsi & Geneletti, 2013 ), etc. into the analysis.…”

“…With the development of location-based services (LBS) in recent years, more and more social media platforms have integrated a LBS module into their blogging tools to enhance the reading experience of travel blogs by providing a new way for tourists to share their travel itinerary ( Stock, 2018 ). These new type of travel blogs are termed as “geo-located travel blogs” ( Kaufmann, Siegfried, Huck, & Stettler, 2019 ). Geo-located travel blogs, originating from the direct editing of tourists, include not only traditional text information, but also rich spatio-temporal label information, allowing a detailed description of tourists' journeys.…”

The Geographies of Expatriates’ Cultural Venues in Globalizing Shanghai: A Geo-Information Approach Applied to Social Media Data Platform

“…As Currid and Williams [54] argued, a recurring challenge to our understanding of the geographies of cultural activities has been a lack of data. Here, we make use of the new opportunities offered by increasingly important social media platforms to identify these locations [1,2,4,5,8,10]. We derive data from four social media apps: Smart Shanghai, Time Out Shanghai, Bon App, and That's Shanghai.…”

“…The purpose of this paper was to analyze the geographies of cultural venues frequently used by expatriates in a globalizing Shanghai. To this end, we used state-of-the-art data and methods put forward in the science and technology of geographic information [1][2][3][4][5][6][7][8][9][10]. Expatriates living in Shanghai constitute a diverse, highly skilled, and mobile workforce [11], and recent research highlights that the presence of this community is both a sign and an enabler of the myriad processes underlying global city development [12][13][14].…”

Learning Patterns of Tourist Movement and Photography from Geotagged Photos at Archaeological Heritage Sites in Cuzco, Peru

“…Prior to such applications, these results were only available through manual processing which does not scale well or update in real-time. Recently, scholars have turned toward social media and visual content analysis using geotagged photos to understand tourist behavior and perceptions at destination hotspots (Zhang and Li 2019, Vu and Ye 2015, Stepchenkov and Zhan 2013, Kaufman and Stettler 2019. At a high level, our work is in a related socio-cultural vein.…”