Email Based Institutional Network Analysis: Applications and Risks

Abstract

Social Network Analysis can be applied to describe the patterns of communication within an organisation. We explore how extending standard methods, by accounting for the direction and volume of emails, can reveal information regarding the roles of individual members. We propose an approach that models certain operational aspects of the organization, based on directional and weighted indicators. The approach is transferable to other types of social network with asymmetrical connections among its members. However, its applicability is limited by privacy concerns, the existence of multiple alternative communication channels that evolve over time, the difficulty of establishing clear links between organisational structure and efficiency and, most importantly, the challenge of setting up a system that measures the impact of communication behavior without influencing the communication behaviour itself.

Keywords

• social network analysis
• email traffic
• centrality
• closeness
• clustering effect
• graph theory
• complex networks
• machine learning
• big data
• human resources management
• organisational dynamics