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Addressing Users’ Privacy Concerns for Improving Personalization Quality: Towards an Integration of User Studies and Algorithm Evaluation

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Intelligent Techniques for Web Personalization (ITWP 2003)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3169))

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Abstract

Numerous studies have demonstrated the effectiveness of personali-zation using quality criteria both from machine learning / data mining and from user studies. However, a site requires more than a high-performance personalization algorithm: it needs to convince its users to input the data needed by the algorithm. Today’s Web users are becoming increasingly privacy-conscious and less willing to disclose personal data. How can the advantages of personalization (and hence, of disclosure) be communicated effectively, and how can the success of such strategies be measured in terms of improved personalization quality? In this paper, we argue for a tighter integration of the HCI and computational issues involved in these questions. We first outline the problems for personalization that arise from the combination of users’ privacy concerns and sites’ current policies of dealing with privacy issues. We then describe the results of an experiment that investigated the effects of changes to a site’s interface on users’ willingness to disclose data for personalization. This is followed by an overview of studies of the sensitivity of mining algorithms to changes in the availability of these types of data. Based on this, we outline a research agenda for future evaluation studies and user agent design.

This research was supported by the Deutsche Forschungsgemeinschaft, Berlin-Brandenburg Graduate School in Distributed Information Systems (DFG grant no. GRK 316/2).

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Authors and Affiliations

  1. Institute of Information Systems, Humboldt-Universität zu Berlin, Spandauer Str. 1, D-10178, Berlin, Germany

    Bettina Berendt & Maximilian Teltzrow

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  1. Bettina Berendt
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  2. Maximilian Teltzrow
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Editors and Affiliations

  1. Center for Web Intelligence School of Computing, DePaul University, Chicago, Illinois, USA

    Bamshad Mobasher

  2. Department of Computer Science, University of Warwick, Coventry, United Kingdom

    Sarabjot Singh Anand

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© 2005 Springer-Verlag Berlin Heidelberg

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Berendt, B., Teltzrow, M. (2005). Addressing Users’ Privacy Concerns for Improving Personalization Quality: Towards an Integration of User Studies and Algorithm Evaluation. In: Mobasher, B., Anand, S.S. (eds) Intelligent Techniques for Web Personalization. ITWP 2003. Lecture Notes in Computer Science(), vol 3169. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11577935_4

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  • DOI: https://doi.org/10.1007/11577935_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-29846-5

  • Online ISBN: 978-3-540-31655-8

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