# Topology of the World Tourism Web
## 2 Materials and Methods
### Theoretical Basis
While the authors primarily discuss satellite tourism accounts, the issue of measurement and analysis problems extends to all macro-level research. The issue of qualitative and quantitative methods in tourism research is also addressed by [17], who emphasize a constructive and interdisciplinary approach for monitoring and managing tourism activities. The importance of SNA use in the analysis of economic and social networks was highlighted during the last crisis [1,2]. One of the first suggestions for combining tourism and SNA extensively discusses the possibilities for SNA application to tourism [18]. In the overview of SNA in tourism [19], authors discuss the relational quality of the data, along with difficulties and limitations of their use, list possible ties between the nodes, discuss measurement scales, and systematize previous research according to used parameters for network description. [PERSON] et al. [20] classify the application of SNA in tourism concerning two mainstream topics: destination management and collaboration between tourism stakeholders and the relationship between tourism and innovation. However, there are also studies that apply SNA to tourism with respect to sustainability (for example, [21,22]), contributing to sustainable tourism trend, as well as papers that reveal flow and behavioral patterns (which may, but do not have to, be related to destination management; for example, [23, 24, 25, 26]). [PERSON] and [PERSON] [7] comprehensively systematize previous research into the following topics: tourism destination networks (real-world relationships, web links, mobility/traveling patterns), attractions/villages spatial networks, tourism dynamics, social media and web navigation patterns, tourism flows, tourism and migration/human mobility, and surveys and others. As a detailed overview of the SNA application in tourism has been provided by [7,18,19] and an extensive review of the research area is beyond the scope of this paper, we kindly encourage the reader to check the referred articles. The motivation for analyzing tourism within the SNA framework is \"understanding the flow of tourism (which) has a source of inspiration related to local and global systems, as well as, strategic marketing in tourism industry development\" [8]. The authors examined changes in the international tourism structure over time. They revealed that network centralization gradually decreased, which leads to the conclusion that tourist destinations (and tourists' preferences) are continually diversifying. Nevertheless, they revealed that some countries remain in top positions over time, with minor variations in ranking, which is in line with previous research [7]. Due to the dynamic aspect of their approach, the authors [8] also learn of the rapid growth of countries that removed travel restrictions on inbound and outbound tourism. The two studies [7,8] also reveal clustering of the countries underlined by geographical and cultural proximity. The importance of geographical and/or cultural patterns also proved important in other SNA applications in tourism flows and movements at the local, country, and regional levels, for example, [27, 28, 29, 30, 31, 32]. The tourism network might exhibit properties similar to the properties of other global networks (as it relates to other global systems [8]). Due to its economic component, the tourism network could show similarities to the trade network [3, 4, 5, 33] or the financial network [34,35]. However, due to its social component, it might resemble migration [36,37] or the education network [38]. Likewise, similarities may exist with the www (World Wide Web) network [39] due to the digitalization processes that support tourism development, as well as with traffic networks [40], which enable travel. According to [10], in SNA application/ there might be biases and idiosyncrasies related to each data set, but the author's critique is mainly pointed to the lack of a systematic approach to determining the \"prevalence of characteristics across ranges of social settings\".