  Accurately analyzing and modeling online browsing behavior play a key role in
understanding users and technology interactions. In this work, we design and
conduct a user study to collect browsing data from 31 participants continuously
for 14 days and self-reported browsing patterns. We combine self-reports and
observational data to provide an up-to-date measurement study of online
browsing behavior. We use these data to empirically address the following
questions: (1) Do structural patterns of browsing differ across demographic
groups and types of web use?, (2) Do people have correct perceptions of their
behavior online?, and (3) Do people change their browsing behavior if they are
aware of being observed? In response to these questions, we find significant
differences in level of activity based on user age, but not based on race or
gender. We also find that users have significantly different behavior on
Security Concerns websites, which may enable new behavioral methods for
automatic detection of security concerns online. We find that users
significantly overestimate the time they spend online, but have relatively
accurate perceptions of how they spend their time online. We find no
significant changes in behavior over the course of the study, which may
indicate that observation had no effect on behavior, or that users were
consciously aware of being observed throughout the study
