Given the importance of developers for the success of mobile platforms, it is critical for vendors to understand how platform innovations impact developer interaction activity and what issues and topics are discussed. An understanding of these issues can help providers improve their release strategies, manage developer expectations, and avoid negative reputation effects. To facilitate this understanding, we are analyzing knowledge ecosystem reactions to change in mobile software development platforms. As part of this work, we have developed a method for gathering information about change events from two sources: endogenous information derived from traces of user interactions within knowledge ecosystems, and exogenous information harvested from official documentation, press releases, and news reports. The method is being applied to data describing interactions on Stack Overflow, the world's most popular social information seeking community for developers. By demonstrating how such data can be processed to highlight periods of rapid change, and how this evidence can be combined with external indicators of change events, we are contributing a new technique to supplement approaches based on direct consultation of system participants.
The Computational Enterprise Science Lab focuses on the design, analysis, and management of complex enterprise systems (e.g. organizations, supply chains, business ecosystems) using information visualization, modeling/simulation, and system science approaches.