Abstract
Over the last years, network analytic methods have been able to provide insights into the structural and dynamic characteristics of systems and phenomena, and they are considered a natural choice when complex systems or phenomena are involved. As a result, these methods have sparked a growing interest in both the tourism and hospitality domains. This chapter will contain an introduction to the concepts, background, and methods of network analysis. After a brief introduction in which the rationale and foundations of network analysis are highlighted, the reader will be provided with a basic series of definitions of the main metrics and with the approach that needs to be followed for a good analysis. The How-To section will contain a worked example, allowing the reader to become familiar with the operative steps of conducting an analysis and interpreting the outcomes. A full research case will then be briefly described and commented on. Lastly, the chapter will conclude with a list of the most relevant and used software packages in this area of work.
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Further Readings and Other Sources
Further Readings and Other Sources
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Baggio, R. (2013). Complexity, Network Science & Tourism. IFITT Education Group Available at http://www.iby.it/turismo/papers/rb_TourNetSci(IFITT).pdf
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Barabási, A. L. (2016). Network science. Cambridge University Press.
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Caldarelli, G., & Chessa, A. (2016). Data science and complex networks: Real case studies with python. Oxford University Press.
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Coscia, M. (2021). The atlas for the aspiring network scientist. IT University of Copenhagen.
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Easley, D., & Kleinberg, J. (2010). Networks, crowds, and markets: Reasoning about a highly connected world. Cambridge University Press.
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Mitchell, M. (2009). Complexity: A guided tour. Oxford University Press.
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Baggio, R. (2022). Network Analysis. In: Egger, R. (eds) Applied Data Science in Tourism. Tourism on the Verge. Springer, Cham. https://doi.org/10.1007/978-3-030-88389-8_21
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