From Videos to URLs: A Multi-Browser Guide To Extract User's Behavior with Optical Character Recognition

Abstract

Tracking users' activities on the World Wide Web (WWW) allows researchers to analyze each user's internet behavior as time passes and for the amount of time spent on a particular domain. This analysis can be used in research design, as researchers may access to their participant's behaviors while browsing the web. Web search behavior has been a subject of interest because of its real-world applications in marketing, digital advertisement, and identifying potential threats online. In this paper, we present an image-processing based method to extract domains which are visited by a participant over multiple browsers during a lab session. This method could provide another way to collect users' activities during an online session given that the session recorder collected the data. The method can also be used to collect the textual content of web-pages that an individual visits for later analysis