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DOBBS: Towards a Comprehensive Dataset to Study the Browsing Behavior of Online Users

Christian von der Weth,M. Hauswirth

Published 2013 in 2013 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT)

ABSTRACT

The investigation of the browsing behavior of users has been a topic of active research since the Web started. However, new online services changed the meaning behind "browsing the Web" and require a fresh look at the problem. Platforms such as YouTube or last. Fm have started to replace the traditional media channels (cinema, television, radio) and media distribution formats (CD, DVD, Blu-ray). Particularly social networks (e.g., Facebook) attracted whole new, particularly less tech-savvy audiences. Advances in mobile technologies made browsing "on-the-move" the norm and changed the user behavior, often being influenced by the user's location and context in the physical world. Commonly used datasets, such as web server access logs or search engines transaction logs, are inherently not capable of capturing the browsing behavior of users in all these facets. DOBBS (DERI Online Behavior Study) is an effort to create such a dataset in a non-intrusive, completely anonymous and privacy-preserving way. DOBBS provides a browser add-on which keeps track of users' browsing behavior. In this paper, we outline the motivation behind DOBBS, describe the add-on and dataset, and present some first results to highlight the strengths of DOBBS.

PUBLICATION RECORD

  • Publication year

    2013

  • Venue

    2013 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT)

  • Publication date

    2013-07-05

  • Fields of study

    Computer Science

  • Identifiers
    DOI 10.1109/WI-IAT.2013.8arXiv 1307.1542
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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