Multi-mediated community structure in a socio-technical network

Abstract

Digital environments for networked learning and professional networks may not comprise one "community:" identification of clusters of affiliated groups of participants that potentially constitute embedded communities is an empirical matter, and one of interest to managers of large learning and professional networks. Also, these socio-technical networks are typically multi-mediated, in that they offer multiple means of participation, each with their own interactional affordances. Different communities may be using the multiple media in different ways. We have developed an analytic framework for extracting events from log files and representing interaction and affiliations at different granularities as needed for analysis. In this paper we show how bimodal networks of actors and media artifacts can be constructed in which directed arcs relate actors to the artifacts they read, write or edit, and how the resulting graphs can be used to detect community structures that extend across different media. We illustrate these ideas with a study that characterizes community structure within the Tapped In network of educational professionals, and how the associations between members of this network are distributed across media (chat rooms, discussion forums and file sharing).