Personal values are measured mainly by self-report tools. This study used people’s online browsing history to assess their personal values (Schwartz, 1992). Participants reported their personal values and uploaded their recent browsing history. Using a machine-learning algorithm, we assessed participants’ personal values based on their web-browsing history. The circular structure of values, which represents the relations between values according to Schwartz’s values theory, was found for self-reported and assessed values alike. This study offers an innovative method for evaluating human values. As not all participants disclosed their browsing history, post-hoc analyses revealed that those who left the study without reporting their browsing data reported higher conservation values (tradition, security, and conformity) than those who shared their browsing history. Also, participants that uploaded irrelevant data reported higher power values than those who shared their browsing history.