Normalized Social Distance: Quantitative Analysis of Religion-Centered Gaming Pages on Social Networks
Abstract
The primary aim of this chapter is to present a new methodological and interpretative framework for the analysis of big social data: in particular, user-generated data obtained from Facebook. The chapter introduces a new, formally-defined, quantitative method called Normalized Social Distance (NSD), developed by the main author of this chapter.
NSD calculates the distances between various social groups, based on the intentional stances expressed by members of these groups in their activities on social networks. NSD results can be visualized in graphs, clusters or dendrograms, and standard methods of network analysis can be applied to them.
As such, NSD provides an opportunity for a distant reading of social network sites, enabling us to formally represent and analyze the structural aspects of big social data. The case study presented in this chapter serves as an example that highlights the use of NSD on a concrete dataset and explains possible further interpretative approaches.
Thematically, the case study focuses on religion-centered gaming pages on social networks. These are Facebook pages providing news, reviews and other gaming-related content and that describe themselves in religious terms and/or state religiously-motivated aims in their descriptions (e.g.
Christian Gamers Alliance, Gamers 4 Christ, Muslim Gamers, Atheist Gamer, etc.). The case study explores 15 religion-centered gaming pages on Facebook and analyzes publicly available data about 10275 of their users.
It aims to explore these pages' audiences and their similarities, differences and affinities through NSD computed from their fans' likes.