Measuring the Effect of Social Communications on Individual Working Rhythms: A Case Study of Open Source Software

This paper proposes novel quantitative methods to measure the effects of social communications on individual working rhythms by analyzing the communication and code committing records in tens of Open Source Software (OSS) projects. Our methods are based on complex network and time-series analysis. We define the notion of a working rhythm as the average time spent on a commit task and we study the correlation between working rhythm and communication frequency. We build communication networks for code developers, and find that the developers with higher social status, represented by the nodes with larger number of outgoing or incoming links, always have faster working rhythms and thus contribute more per unit time to the projects. We also study the dependency between work (committing) and talk (communication) activities, in particular the effect of their interleaving. We introduce multi-activity time-series and quantitative measures based on activity latencies to evaluate this dependency. Comparison of simulated time-series with the real ones suggests that when work and talk activities are in proximity they may accelerate each other in OSS systems. These findings suggest that frequent communication before and after committing activities is essential for effective software development in distributed systems.