Interaction Analytics of Software Factory Recordings

• Other Authors: Pressler, Daniel (Author)
• Format: Dissertation
• Language: English
• Published: 2018
• Subjects: Electrical engineering
• Online Access: http://hdl.handle.net/2286/R.I.51586

abstract: A human communications research project at Arizona State University aurally recorded the daily interactions of aware and consenting employees and their visiting clients at the Software Factory, a software engineering consulting team, over a three year period. The resulting dataset contains valuable insights on the communication networks that the participants formed however it is far too vast to be processed manually by researchers. In this work, digital signal processing techniques are employed to develop a software toolkit that can aid in estimating the observable networks contained in the Software Factory recordings. A four-step process is employed that starts with parsing available metadata to initially align the recordings followed by alignment estimation and correction. Once aligned, the recordings are processed for common signals that are detected across multiple participants’ recordings which serve as a proxy for conversations. Lastly, visualization tools are developed to graphically encode the estimated similarity measures to efficiently convey the observable network relationships to assist in future human communications research. === Dissertation/Thesis === Masters Thesis Electrical Engineering 2018