In real-life social networks it is likely that social interaction behavior changes in continuous time. These changes can occur gradually or instantaneously. This project aims to develop quantitative methods for identifying such gradual changes (e.g., using moving window techniques) or instantaneous changes (e.g., using change-point detection algorithms) of social network behavior. These methods have been used to study changes in social interaction behavior during NASA’s famous Apollo 13 mission to the moon (“Houston, we’ve had a problem!”).modeling (Bayesian and classical), artificial intelligence, and the social and behavioral sciences. We develop novel statistical and data scientific methods for social network research to better understand social network dynamics from empirical data.