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Description
Our lives are documented and facilitated by the internet. Given that an increasing proportion of time is being spent online, search and browsing history offers a unique frame of reference to conduct a qualitative study since it contains individual goals,

Our lives are documented and facilitated by the internet. Given that an increasing proportion of time is being spent online, search and browsing history offers a unique frame of reference to conduct a qualitative study since it contains individual goals, day-to-day experiences, illicit thoughts, and questions, all while capturing sentiments rather than statistics. Seeing this recorded daily activity mapped out over the course of several years would hopefully provide a startling reminder of how life can be accurately and simply described as a series of constantly evolving interests and intentions, as well as give a sense of how exhaustively massive internet companies collect private information online. The search engine giant Google offers its users the transparency and freedom to export and download an archive of their web activity through a service known as Google Takeout. We propose using this service to empower ordinary individuals with Google accounts by developing a comprehensive and qualitative approach to understanding and gaining insights about their personal behavior online. In this paper, we first define and analyze the need for such a product. Then we conduct a variety of intent and interest-sensitive computational analysis methods on a sample browser history to explore and contextualize emergent trends, as a proof of concept. Finally, we create a blueprint for building an interactive application which uses our approach to generate dynamic dashboards and unique user profiles from search and browsing data.
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Barrett Honors College theses and creative projects are restricted to ASU community members.

Details

Title
  • An Exploratory Analysis of Individual Long-Term Google Search and Browsing History
Contributors
Date Created
2018-12
Resource Type
  • Text
  • Machine-readable links