Using big data and social network analysis for cultural tourism planning in Hakka villages

Abstract

Traveling in a Hakka village, the tourist can feel the culture of the Hakka in Taiwan and see traditional drama, artwork, handicrafts, and foods. The current trend in tourism planning is to incorporate online word of mouth into route design. This paper aims to examine common characteristics of Hakka village tourism development, identifying the need for planning and offering a model of the directions planning might take. It begins with big data collection of the online service and combines that with social network analysis. The results indicated that tourism planning with user's online search strategy will provide a better and more precise tour service. It is suggested that the government should set up the tour service center at the location identified as being in the structural hole of the tourism network. As cultural tourism continues to expand, big data applications will offer new opportunities and challenges to tourism planning.

Digital innovations in tourism: the perceptions of stakeholders

“…Additionally, some advocate the use of digital technologies in tourism planning, e.g. big data and social network analysis data (Hu et al ., 2021).…”

New entrants for attractions network evolution

“…The Pink subgroup is composed of the attractions with the highest betweenness and degree centralities (A6, A7, A18 and A32). Attractions with greater centrality are usually more associated with the destination brand and are more relevant to the destination attractiveness (Aastard et al, 2015; Hu et al, 2020; Leung et al, 2012; Stienmetz and Fesenmaier, 2018). This perspective seems to be confirmed, since the Pink subgroup attractions are traditional and highly associated with the destination image, such as Minimundo (A7), Rua Coberta (A18) and Lago Negro (A6).…”

“…The central nodes in a network of tourist attractions are relevant to assess the overall destination competitiveness (Stienmetz and Fesenmaier, 2018). Liu et al (2017) and Hu et al (2020) associate the actor’s degree centrality to their attractiveness to tourists. Attractions with a higher degree centrality have a greater capacity to arouse interest and attract tourists, being central for the experience provided by the destination (Leung et al, 2012; Stienmetz and Fesenmaier, 2018).…”

Spatio-Temporal Distribution of Tourism Flows and Network Analysis of Traditional Villages in Western Hunan

“…Early studies on tourism flows relied mainly on questionnaire surveys and statistical yearbooks, making it difficult to obtain data, especially for traditional villages. Research on traditional village tourism has therefore focused on the value and conservation of tourism resources, tourism development, tourism impact and management, and tourism problems and countermeasures [9][10][11][12][13]. In recent years, information and communication technology has developed rapidly, and the Internet has become an important platform for users to obtain and share travel information.…”