Academic Publications: Communication

TeCFlow - A Temporal Communication Flow Visualizer for Social Network Analysis

Peter A. Gloor, MIT Center for Coordination Science, Yan Zhoa
ACM CSCW Conference, 2004

This paper introduces an approach for organizational redesign and optimization of communication flows basedon temporal analysis of communication patterns in groups of people. Our Temporal Communication Flow Visualizer automatically generates interactive movies of communication flows among individuals by mining email log files and other communication archives. Combining those movies with measures of social network analysis such as the change over time in group between centrality (GBC) and group density leads to deep insights into organizational dynamics. In addition we have defined a contribution index, which measures the activity of an individual as a sender and receiver of messages relative to a team. Based on these findings we can make predictions on the productivity of teams and suggest interventions for improved performance.  

Paper in PDF Format (99K)

Topics: Change, Communication, Information Technology, Organization, Performance, Social Media

Visualization of Communication Patters in Collaborative Innovation Networks

Scott Dynes, Yan Zhoa, Peter Gloor, Rob Laubacher
CDS Working Paper Series 2003-1

Collaborative Innovation Networks (COINs) are groups of self-motivated individuals from various parts of an organization or from multiple organizations, empowered by the Internet, who work together on a new idea, driven by a common vision. In this paper we report first results of a project that examines innovation networks by analyzing the e-mail archives of some W3C (WWW consortium) working groups. These groups exhibit ideal characteristics for our purpose, as they form truly global networks working together over the Internet to develop next generation technologies. We first describe the software tools we developed to visualize the temporal communication flow, which represent communication patterns as directed acyclic graphs. We then show initial results, which revealed significant variations between the communication patterns and network structures of the different groups. We were also able to identify distinctive communication patterns among group leaders, both those who were officially appointed and other who were assuming unofficial coordinating roles.

Paper in PDF Format (343K)

Topics: Collaboration, Communication, Innovation, Knowledge Management, Social Media