Uncovering multi-mediated associations in socio-technical networks

Kar Hai Chu, University of Hawaiʻi at Mānoa
Daniel D. Suthers, University of Hawaiʻi at Mānoa
Devan Rosen, Ithaca College

Abstract

People interact in a variety of ways, and often choose what media to use based on the relationships they have with their interlocutors. Similarly, there are different ways through which people are associated in sociotechnical networks or "online communities." This paper reports a study that characterizes how the associations between members of a socio-technical network-the Tapped In network of educational professionals-are distributed across various asynchronous media, and what clusters of associations suggest about community structure within this network. The paper also illustrates an application of an analytic framework we are developing for extracting and analyzing interaction and affiliation data from log files. Affiliation networks of actors and media artifacts were constructed in which directed arcs relate actors to the artifacts they read, write or edit. Visualization of these graphs and associated sociometrics demonstrate how affiliations between participants are distributed differently across media types, reflecting the different roles these media play, and revealing community clusters within the network. © 2012 IEEE.