Scale, Time, and Activity Patterns: Advanced Methods for the Analysis of Online Networks

Abstract

Social media and web technologies have become a prominent source of data for researchers interested in the analysis of social interactions and communication dynamics. Online data help us revisit old theoretical accounts of interpersonal influence, diffusion processes, or group formation; they offer, in other words, an empirical domain in which to test and develop social theory. The analysis of online networks, however, also creates methodological challenges that are new to researchers used to employing more traditional measurement instruments like surveys or name generators, which are tailored to yield smaller and more static data. One difference, for instance, is that the higher temporal resolution of online data demands defining some rules to aggregate activity in the form of network ties. Large network data also requires applying methods that can offer a simplified map of the structure, or that allow filtering irrelevant, noisy information and retain only the significant connections. This chapter offers an overview of some of those methods, illustrating how advanced techniques help us manage and analyze online networks and develop our theoretical understanding of social interactions and communication in the digital age.

Keywords: network science; digital data; methods; communication