Internet technology allows web site administrators to monitor users visiting their sites. In the beginning the basic protocol used for the web (http) did not consider the concept of a session. It was impossible to recognise whether two requests came from the same user. Developers then found ways to follow visitors and implemented logins and shopping carts. These solutions included cookie session IDs encoded in the URL, or more recently the creation of a virtual host for each visitor. These mechanisms have also been used for statistical purposes, to study the behaviour of groups of users (group profiling) and to predict the behaviour of a specific user (user profiling).
Usually, collecting information is not in itself reprehensible; however, the use of the data is more critical. One can never be sure if it will be used for statistics (on anonymised data), for one-to-one marketing, or be sold to a third party. The W3 Consortium has published a standard called P3P, giving web site administrators the possibility to declare their policy regarding privacy in a machine readable format. Unfortunately, most people are not yet aware of the sensitivity of collected data; there is therefore no wide resistance to the creation of huge interoperable databases.
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References
Agre, P. E., Rotenberg, M, Technology and Privacy: The New Landscape, MIT, Cambridge, Massachusetts, 2001.
Berendt B., Mobasher, B. and Spiliopoulou, M., ‘Web Usage Mining for E-Business Applications’, ECML/PKDD-2002 Tutorial ‘Text Mining and Internet Content Filtering’, Helsinki, 19 August 2002.
Berry, M.J.A. and Linoff, G., Mastering data mining: the art and science of customer relationship management, Wiley, New York, 2000.
Bertino, E., Nai F., I., Parasiliti P. L., ‘A framework for evaluating privacy preserving data mining algorithms’, Data Mining and Knowledge Discovery, Vol. 2, No. 11, Springer publ., New York, 2005, pp. 121–154.
Clarke, R., ‘P3P Re-visited’, 2001. Available at: http://www.anu.edu.au/people/Roger.Clarke/DV/P3PRev.html
Cranor, L.F., ‘ ‘I Didn’t Buy it for Myself’. Privacy and E-commerce Personalization’, Proceedings of the 2003 ACM Workshop on Privacy in the Electronic Society, ACM Press, Washington DC, 2003, pp. 111–117.
Coyle, K., ‘P3P, Pretty Poor Privacy? A social analysis of the platform for privacy preferences P3P’. Available at: www.kcoyle.net/p3p.html
Dholakia, N., Zwick, D., ‘Privacy and consumer agency in the information age: between prying profilers and preening webcams’, Journal of Research for Consumers, Vol. 1, No.1, online journal sponsored by UWA business school and the graduate school of Management. Available at: http://web.biz.uwa.edu.au/research/jrconsumers/academic/academic_article.asp?IssueID=9&ArticleID=3
EPIC, ‘Pretty Poor Privacy: An Assessment of P3P and Internet Privacy’, June 2000. Available at http://www.epic.org/reports/prettypoorprivacy.html
EPIC Digest 06/05/2001. Available at http://www.privacy.org/digest/epic-digest06.05.01.html
Jiang, X., ‘Safeguard Privacy in Ubiquitous Computing with Decentralized Information Spaces: Bridging the Technical and the Social’, paper presented at ‘Privacy in Ubicomp’, Workshop on socially informed design of privacy-enhancing solutions in ubiquitous computing, Sweden, September 29, 2002. Available at: http://guir.berkeley.edu/pubs/ubicomp2002/privacyworkshop/papers/jiang-privacyworkshop.pdf
Garfinkel, S. and Spafford, G., Web Security, Privacy & Commerce. O’Reilly, second edition, 2002.
Godoy, D., Amandi, A., ‘User profiling for web page filtering’, IEEE Internet Computing, Vol. 9, No. 4, IEEE Computer Society, Wash. DC, 2005, pp 56–64.
Hyung, Joon Kook, ‘Profiling multiple domains of user interests and using them for personalized web support’, Lecture notes in computer science, Vol. 3645, Advances in Intelligent Computing, International Conference on Intelligent Computing, ICIC Hefei, China, August 23–26, 2005, Proceedings, Part II, Springer, Berlin - Heidelberg, 2005, pp. 512–520.
Hildebrandt, M., ‘Profiling: From Data to Knowledge, The challenges of a crucial technology’, DuD, Datenschutz und Datensicherheit, Vol. 30, No. 9, Vieweg-Verlag, Wiesbaden, 2006, pp. 548–552.
Masand, B., Spiliopoulou, M. (eds), ‘Web usage analysis and user profiling’, international WEBKDD’99 workshop, San Diego, CA, USA, August 15, 1999; revised papers, Lecture Notes of Computer Science, LNAI, Vol. 1836, Springer, Berlin-Heidelberg, 2000.
Mobasher, B., Cooley, R., Srivastava, J., ‘Automatic Personalization Based on Web Usage Mining’, Communications of the ACM, Vol. 43, No. 8, ACM Press, New York, 2000, pp. 141–151.
Oliveira, S.R.M. and Zaiane, O.R., ‘Toward standardization in privacy preserving data mining’, Proceedings of the ACM SIGKDD 3rd Workshop on Data Mining Standards, 2004, pp. 7–17. Available at: http://www.cs.ualberta.ca/zaiane/postscript/dm-ssp04.pdf
Plant, S., Zeros + Ones: Digital Women + The New Technoculture, Doubleday, New York, first edition, 1997.
Poster, M., The Second Media Age. Cambridge Polity Press, Cambridge, 1995.
Riedl, ‘Personalization and Privacy’, IEEE Internet Computing, Vol. 5, No. 6, IEEE Computer Society, Washington D.C., 2001, pp. 29–31.
Schreuders, E., Data mining, de toetsing van beslisregels en privacy (Data mining examining decision rules and privacy), ITeR, No. 48, Sdu Pu, Den Haag, 2005.
Srivastava, J., Cooley, R., Deshpande, M., Tan, P-N., ‘Web Usage Mining: Discovery and Applications of Usage Patterns from Web Data’, ACM SIGKDD Explorations, Vol. 1, No. 2, ACM Press, New York, 2000, pp. 12–23.
Treiblmaier, H., Madlberger, M, Knotzer, N., Pollach, I., ‘Evaluating Personalization and Customization from an Ethical point of View: an empirical study’, Proceedings of the 37 th Hawaii International Conference on System Science, Big Island, HI, USA. IEEE Computer Society, 2004.
Vriens, M., Grigsby, M. ‘Building Online Customer-Brand Relationships’, Marketing Management, Vol. 10, No. 4, American Marketing Association publications, Chicago, 2001, pp. 34–39.
Welling, L., Thomson, L., PHP and MySQL Web Development. Sams, Indianapolis, Indiana, March 2001.
Won, K., ‘Personalization: Definition, Status and challenges ahead’, Journal of Object Technology, Vol. 1, No. 1, Chair of software engineering at EHZ Zurich, 2002, pp. 29 – 40. Available at www.jot.fm/issues/issue_2002_05/column3
Xu, G., et al., ‘Towards user profiling for web recommendation’, Australian Conference on Artificial Intelligence, Proceedings. Lecture Notes in Computer Science, Vol. 3809, Springer, Berlin - Heidelberg, 2005, pp. 415–424.
Zwick, D., Dholakia, N., ‘Whose Identity is it anyway. Consumer representation in the age of database marketing’, Journal of Macromarketing, Vol. 24, No. 1, Sage Publications, New York, London, Delhi, 2004, pp. 31–43.
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Benoist, E. (2008). Collecting Data for the Profiling of Web Users. In: Hildebrandt, M., Gutwirth, S. (eds) Profiling the European Citizen. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-6914-7_9
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