Suchergebnisse

Purpose
The purpose of this paper is to focus on understanding the factors which affect the social interaction in the case of Facebook. Many authors point out the great potential of these networks for social interaction and as conduits of information. However, studies show that the topology of the network is disconnected, consisting of small sub-networks that make Facebook unsuitable for disseminating information. This situation has created the need to introduce exogenous factors, aimed at boosting and providing cohesion to the network structure. In this context, the authors test the following question: how exogenous and endogenous factors contribute to encouraging social interaction on Facebook.


Design/methodology/approach
For the analysis of social interaction on Facebook, a population consisting of all the followers of the walls of ten corporate social networks was used. From the total 269,424 users analyzed, a stratified sample of 132 followers was obtained and networks were built for each of them. The authors then proceeded to search for each follower's friends and friends of friends to build the social network up to the fourth level, obtaining a total of 132 subnets with 1,628,074 links between them. To determine the impact of both exogenous and endogenous factors in the interaction of the network the authors performed a causal analysis.


Findings
The results obtained from this study provide empirical evidence on the adequacy of companies' dynamization measures used and how exogenous and endogenous factors influence the social interaction on Facebook. Thus, the results show that exogenous factors, such as the activity of the community manager and the digital marketing investment in the network, do not have a significant effect on the interaction. On the other hand, endogenous factors, such as network density and clustering, have a positive effect on the trigger of social interaction between the followers. Therefore, companies must consider the importance of the structural factors that characterize network followers, such as density or clustering coefficient, to be able to interpret and optimize them to obtain higher levels of social interaction.


Originality/value
This is one of a few papers that examine interactions in social network sites (SNS), particularly in corporate network sites in Facebook. The results expose the importance for organizations to have reliable information on the patterns of interaction to properly manage the resources allocated for this purpose in SNS.