Automatic Generation of Social Network Data from Electronic-Mail Communications
Abstract
Most organizations have formal and informal elements. Formal structures are usually documented in organizational charts showing chain of command, levels of authority, and personnel resources. The actual effectiveness of the organization or specific individuals may actually depend on informal structures and internal communication networks. These are by definition personality-dependent and may provide significant insight into how work actually gets done within the organization. Effective leaders will want insight into these informal structures for various reasons. Inefficient decision-making or staffing processes may result in unnecessary or redundant communications, chokepoints, or single points of failure, each of which can either delay decisions or degrade the quality of those decisions. Further, sudden changes in the informal structures may indicate underlying stresses within the organization, interpersonal conflicts, or behavioral problems that may significantly disrupt the mission effectiveness or morale of the organization. Documenting these informal structures and networks can be achieved through a variety of means, often through personal interviews or direct observation, both of which are difficult and time consuming. In this paper, we describe a method of automatically generating social network data using electronic mail messaging logs. Performance is demonstrated using three months of real data from a medium sized organization.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jun 01, 2005
- Accession Number
- ADA464107
Entities
People
- Gilbert L. Peterson
- Jason Yee
- Robert F. Mills
- Summer E. Bartczak
Organizations
- Air Force Institute of Technology