Abstract
Rapid growth of data intensive digital services are creating potential risks of violating consumer centric data privacy. Protection of data privacy is becoming one of the key challenges for most of the big data business entities. Due to thank of big data, recommendation and personalization are becoming very popular in digital space. However it is hard to find a well-defined boundary which illustrates privacy threat to consumers’ in relation with improving already opted-in communication services.
In this paper, we initiated identifying key indicators for consumer configured privacy policy in relation with personalized services taking into consideration that “Privacy is a tool for balancing personalization”. We survey user attitudes towards privacy and personalization and discovered key indicators for configuring privacy policy by analyzing survey data about privacy concern and data sharing attitude of the consumers. We found that consumers did not want to stop using social media based communication services due to privacy risks. Moreover, consumers have attitude of sharing their data, provided that appropriate personalization features are in place.
J. Rana—The work has been carried out as part of an academic research project and does not necessarily represent Telenor views and positions.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Rana, J.: Improving Group Communication by Harnessing Information from Social Networks and Communication Services, ser. Licentiate thesis/Luleå University of Technology (2011). http://books.google.se/books?id=TLa7XwAACAAJ
Rana, J., Hallberg, J., Synnes, K., Kristiansson, J.: Harnessing the cloud for mobile social networking applications. Int. J. Grid High Perform. Comput. (IJGHPC) 2(2), 1–11 (2010)
Synnes, K., Kranz, M., Rana, J., Schelén, O., Nilsson, M.: User-centric social interaction for digital cities. In: Creating Personal, Social, and Urban Awareness through Pervasive Computing, pp. 318–346 (2013)
Chellappa, R.K., Sin, R.G.: Personalization versus privacy: an empirical examination of the online consumers dilemma. Inf. Technol. Manag. 6(2–3), 181–202 (2005)
Appendix 1 - defination of variables, 8 July 2015. https://www.dropbox.com/s/b4xzgfyper3kyms/Attitide_Scenario_Variables_Definition.pdf?dl=0
Michael, R.S.: Crosstabulation & chi square. Indiana University, Bloomington (2001). http://www.indiana.edu/~educy520/sec5982/week_12/chi_sq_summary011020.pdf. (Accessed on 15 April 2016)
Appendix 2 - association test using crosstabulation, 20 April 2016. https://www.dropbox.com/s/1ze7rv0klc9vi6c/Final_Results_Discussion.pdf?dl=0
Kenneally, E., Claffy, K.: Dialing privacy and utility: a proposed data-sharing framework to advance internet research. IEEE Secur. Priv. 8(4), 31–39 (2010)
Olivero, N., Lunt, P.: Privacy versus willingness to disclose in e-commerce exchanges: the effect of risk awareness on the relative role of trust and control. J. Econ. Psychol. 25(2), 243–262 (2004). http://EconPapers.repec.org/RePEc:eee:joepsy:v:25:y:2004:i:2:p:243-262
Clifton, C., Kantarcioǧlu, M., Doan, A., Schadow, G., Vaidya, J., Elmagarmid, A., Suciu, D.: Privacy-preserving data integration and sharing. In: Proceedings of the 9th ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery, DMKD 2004, pp. 19–26. ACM, New York (2004). http://doi.acm.org/10.1145/1008694.1008698
Belanger, F., Hiller, J.S., Smith, A.J.: Trustworthiness in electronic commerce: the role of privacy, security, and site attributes. J. Strateg. Inf. Syst. 11, 245–270 (2002)
Greenleaf, G.: Five years of the APEC privacy framework: failure or promise? Comput. Law Secur. Rev. 25(1), 28–43 (2009). http://www.sciencedirect.com/science/article/pii/S0267364908001714
Chen, X., Orlowska, M., Li, X.: A new framework of privacy preserving data sharing. In: Proceedings of the IEEE ICDM Workshop on Privacy and Security Aspects of Data Mining Press, pp. 47–56 (2004)
Toch, E., Wang, Y., Cranor, L.F.: Personalization and privacy: a survey of privacy risks and remedies in personalization-based systems. User Model. User Adap. Inter. 22(1–2), 203–220 (2012). http://dx.doi.org/10.1007/s11257-011-9110-z
Culnan, M.J., Armstrong, P.K.: Information privacy concerns, proceduralfairness, and impersonal trust: an empirical investigation. Organ. Sci. 10(1), 104–115 (1999). http://dx.doi.org/10.1287/orsc.10.1.104
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Noori, S.R.H., Hossain, M.K., Rana, J. (2016). Key Indicators for Data Sharing - In Relation with Digital Services. In: Tan, Y., Shi, Y. (eds) Data Mining and Big Data. DMBD 2016. Lecture Notes in Computer Science(), vol 9714. Springer, Cham. https://doi.org/10.1007/978-3-319-40973-3_35
Download citation
DOI: https://doi.org/10.1007/978-3-319-40973-3_35
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-40972-6
Online ISBN: 978-3-319-40973-3
eBook Packages: Computer ScienceComputer Science (R0)