<b>Research Note</b>—Towards Dynamic Visualization for Understanding Evolution of Digital Communication Networks

The capabilities offered by digital communication are leading to the evolution of new network structures that are grounded in communication patterns. As these structures are significant for organizations, much research has been devoted to understanding network dynamics in ongoing processes of electronic communication. A valuable method for this objective is Social Network Analysis. However, its current focus on quantifying and interpreting aggregated static relationship structures suffers from some limitations for the domain of analyzing online communication with high volatility and massive exchange of timed messages. To overcome these limitations, this paper presents a method for event-based dynamic network visualization and analysis together with its exploratory social network intelligence software Commetrix. Based on longitudinal data of corporate email communication, the paper demonstrates how exploration of animated graphs combined with measuring temporal network changes identifies measurement artifacts of static network analysis, describes community formation processes and network lifecycles, bridges actor level with network level analysis by analyzing the structural impact of actor activities, and measures how network structures react to external events. The methods and findings improve our understanding of dynamic phenomena in online communication and motivate novel metrics that complement Social Network Analysis.

• 저널Information Systems Research · 19(3) · 335–350
• 토픽Complex Network Analysis Techniques · Statistical and Nonlinear Physics
• DOI10.1287/isre.1080.0191
• 저자Matthias Trier