chapter  9
17 Pages

Data collection for social network analysis in tourism research


Introduction Interest in social networks and their analysis can be traced to the recognition that social relations affect human behaviour at multiple levels (Freeman 2004). It is not only that relations matter, but that considering human agents bereft of such relations (as independent of one another) biases our comprehension of their agency. Humans do not act as independent units and to account for their actions it is essential to capture the relations that create their social context. For instance, over the last decade, evidence has emerged of second and even third degree network effects on our conscious and unconscious choices (Fowler and Christakis 2009). Human agents are not only affected by their friends, but the friends of their friends and potentially even those further away on what is termed their horizon of observability (Friedkin 1998). Social animals have been hard wired to cooperate in groups of about 150 individuals (Hill and Dunbar 2003), and while in contemporary western societies humans interact with a multitude of this number, they lack the cognitive capacity to build strong ties beyond a select few. In other words, the relations humans maintain, are indicative of conscious or subconscious choices and knowing more about these relations can help us understand human action better. By employing social network analysis (SNA) one can also examine the relations between collective agents, such as organizations. Obviously, any claims on the effect of networks on social interactions are inherently contingent on the type of agents and type of relations that one examines. The study of social networks has fundamentally benefitted from the development of a range of new descriptive and inferential statistical tools that acknowledge the dependence inherent in network relations (Scott and Carrington 2013).1 SNA is premised on graph theory mathematics, network science statistics and relational sociology which combined provide the theoretical and methodological foundations to the field. Social networks which stem out of the process to create, access, diffuse, absorb and use information that is dispersed across a wide range of human and organizational actors are understood as knowledge networks. The body of network studies with an explicit or implicit focus on knowledge has grown considerably in the last decade (Phelps, Heidl and Wadhwa 2012), but rarely

with examples from the tourism domain. The focus of this chapter is to discuss the types of data and the process of data collection pertinent to social networks in general and knowledge networks in particular. Tourism domain examples in this chapter employ social network analysis on areas where knowledge networks implicitly underpin transactions between actors.