Title: Mining social network data for personalisation and privacy concerns: a case study of Facebook's Beacon

Authors: Arshad Jamal; Jane Coughlan; Muhammad Kamal

Addresses: Department of Information Systems and Computing, Brunel University, Kingston Lane, Uxbridge, Middlesex, UB8 3PH, UK ' Department of Information Systems and Computing, Brunel University, Kingston Lane, Uxbridge, Middlesex, UB8 3PH, UK ' Business School, Brunel University, Kingston Lane, Uxbridge, Middlesex, UB8 3PH, UK

Abstract: The popular success of online social networking sites (SNS) such as Facebook is a hugely tempting resource of data mining for businesses engaged in personalised marketing. The use of personal information, willingly shared between online friends' networks intuitively appears to be a natural extension of current advertising strategies such as word-of-mouth and viral marketing. However, the use of SNS data for personalised marketing has provoked outrage amongst SNS users and radically highlighted the issue of privacy concern. This paper inverts the traditional approach to personalisation by conceptualising the limits of data mining in social networks using privacy concern as the guide. A qualitative investigation of 95 blogs containing 568 comments was collected during the failed launch of Beacon, a third party marketing initiative by Facebook. Thematic analysis resulted in the development of taxonomy of privacy concerns which offers a concrete means for online businesses to better understand SNS business landscape - especially with regard to the limits of the use and acceptance of personalised marketing in social networks.

Keywords: social networking sites; SNS; social networks; Facebook; privacy concerns; thematic analysis; taxonomy; qualitative; blogs; inductive; data mining; personalisation; Beacon; personalised marketing.

DOI: 10.1504/IJBIS.2013.054334

International Journal of Business Information Systems, 2013 Vol.13 No.2, pp.173 - 198

Available online: 05 Jun 2013 *

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