Although we may complain about meetings, they are an essential part of an information worker's work life. Consequently, busy people spend a significant amount of time scheduling meetings. We present Calendar.help, a system that provides fast, efficient scheduling through structured workflows. Users interact with the system via email, delegating their scheduling needs to the system as if it were a human personal assistant. Common scheduling scenarios are broken down using well-defined workflows and completed as a series of microtasks that are automated when possible and executed by a human otherwise. Unusual scenarios fall back to a trained human assistant executing an unstructured macrotask. We describe the iterative approach we used to develop Calendar.help, and share the lessons learned from scheduling thousands of meetings during a year of real-world deployments. Our findings provide insight into how complex information tasks can be broken down into repeatable components that can be executed efficiently to improve productivity.

The arrival of a new interest-sharing network, So.cl, provides for a new opportunity to explore human behavior as it relates to constructing public contributions and receiving community response. This study looks at archival data in order to better understand how types of shared content receive interaction from others. The results suggest that a So.cl user should include more photos and less links on their post to increase the quantity of likes and comments the community gives to the post, among other discoveries.