Abstract
The applications of social network analysis to the world tourism network are scarce, and a research update is long overdue. The goal of this research is to examine the topology of the world tourism network and to discuss the meaning of its characteristics in light of the current situation. The data used for the analysis comprise 193 target countries, 242 source countries, and 17,022 links, which is an overall 1,448,285,894 travels in 2018. Social network analysis is applied to the data to determine network topological and diffusion properties, as well as the network structure and its regularities (does it behave more as a social or a technological/biological network?). While results presented in this paper give a thorough insight into the world tourism network in the year 2018, they are only a glimpse in comparison to the possibilities for further research.
Highlights
Complex systems, such as tourism, may be observed from the social network analysis (SNA) perspective
The goal of this research is to examine the topology of the world tourism network and to discuss the meaning of its characteristics in light of the current situation
Tourism refers to a specific set of activities taken by a traveler when taking a trip to a destination outside his usual environment for a limited duration and for any main purpose except for employment [9]
Summary
Complex systems, such as tourism, may be observed from the social network analysis (SNA) perspective. The importance of SNA use in the analysis of economic and social networks arose during the last crisis [1,2]. Miguéns and Mendes [6] studied inbound and outbound tourism based on international tourist arrivals for the year 2004. Lozano and Gutiérrez [7] examined the top outbound vs inbound countries in the tourism network on the global scale for the years 2013 and 2014. Seok et al [8] examined the international tourism flow for the period from 2002 to 2014 based on UN World Tourism Organization (UNWTO) data for 218 listed countries. In addition to the complexity of the network, tourism is a dynamic phenomenon, indicating network growth and development over time. Findings from the previous years may not be valid over a longer period of time
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