TJTSM65 Information Privacy (5 cr)

Study level:
Advanced studies
Grading scale:
0-5
Language:
English
Responsible organisation:
Faculty of Information Technology
Curriculum periods:
2017-2018, 2018-2019, 2019-2020

Description

Content

The proliferation of various information systems and applications has enabled large scale collection and analysis of individuals’ personal information. Social network sites, location services, e-commerce sites, etc. are using multiple sources to collect data and construct user profiles, to better understand users. For example, Facebook is not only tracking the information users share on the site, but also users’ browsing habits. Such data collection may allow companies to cater their services and provide personalized products, but it may raise concerns about privacy. In this course we provide a thorough investigation of privacy in the information age. We begin by scrutinizing the concept of information privacy, and the pros and cons of personal information usage and privacy protection. We discuss real-life privacy related case. We also discuss academic research on privacy, examine both the theory and research methodology. Social network analysis, an important data analysis method, will also be introduced.

Completion methods

Learning Activities include lectures, which focuses on theory, policy and management issues; Paper discussion that discuss privacy related academic papers in detail. What are the research questions, how the studies address the questions, what are the contributions, etc.. Students should read the designated papers before attending the classes; And case discussions on real-life cases, which will be used to illustrate the concepts, theories, and practices covered in the course.

Assessment details

Individual Assignments 20%; Group Project: Project Presentation 15%; Group Project: Project Report 15%; Final Exam 50%

Learning outcomes

Students will have a good understanding of how people view information privacy from different perspectives and the implications of these perspectives. Students will develop skills in analyzing real cases. Students will gain a good knowledge about academic research related to privacy. Students will learn from the research papers and be more competent in designing their own research.

Description of prerequisites

This course assumes that you have already completed your bachelor’s studies and you are currently doing your master’s or doctoral studies.

Literature

  • Acquisti, A., Brandimarte, L., & Loewenstein, G. (2015). Privacy and human behavior in the age of information. Science, 347(6221), 509-514.
  • Özpolat, K., Gao, G., Jank, W., & Viswanathan, S. (2013). Research note—The value of third-party assurance seals in online retailing: An empirical investigation. Information Systems Research, 24(4), 1100-1111.
  • Chellappa, R. K., & Sin, R. G. (2005). Personalization versus privacy: An empirical examination of the online consumer’s dilemma. Information Technology and Management, 6(2-3), 181-202.
  • Westin, A. F. (2003). Social and political dimensions of privacy. Journal of Social Issues, 59(2), 431-453.
  • Bollen, J., Mao, H., & Zeng, X. (2011). Twitter mood predicts the stock market. Journal of Computational Science, 2(1), 1-8.
  • Hann, I. H., Hui, K. L., Lai, Y. L., Lee, S. Y. T., & Png, I. P. (2006). Who gets spammed?. Communications of the ACM, 49(10), 83-87.
  • Angst, C. M., & Agarwal, R. (2009). Adoption of electronic health records in the presence of privacy concerns: The elaboration likelihood model and individual persuasion. MIS Quarterly, 33(2), 339-370.
  • Goh, K. Y., Hui, K. L., & Png, I. P. (2015). Privacy and Marketing Externalities: Evidence from Do Not Call. Management Science, 61(12), 2982-3000.
  • Krishnamurthy, B., & Wills, C. E. (2009, August). On the leakage of personally identifiable information via online social networks. In Proceedings of the 2nd ACM workshop on Online Social Networks (pp. 7-12). ACM.
  • Johnson, E. J., & Goldstein, D. (2003). Do defaults save lives?. Science, 302(5649), 1338-1339.
  • John, L. K., Acquisti, A., & Loewenstein, G. (2011). Strangers on a plane: Context-dependent willingness to divulge sensitive information. Journal of Consumer Research, 37(5), 858-873.
  • Awad, N. F., & Krishnan, M. S. (2006). The personalization privacy paradox: an empirical evaluation of information transparency and the willingness to be profiled online for personalization. MIS Quarterly, 13-28.
  • Krishnamurthy, B., & Wills, C. (2009, April). Privacy diffusion on the web: a longitudinal perspective. In Proceedings of the 18th International Conference on World Wide Web (pp. 541-550). ACM.
  • Hui, K. L., Teo, H. H., & Lee, S. Y. T. (2007). The value of privacy assurance: an exploratory field experiment. MIS Quarterly, 19-33.
  • Tsai, J. Y., Egelman, S., Cranor, L., & Acquisti, A. (2011). The effect of online privacy information on purchasing behavior: An experimental study. Information Systems Research, 22(2), 254-268.
  • Smith, H. J., Dinev, T., & Xu, H. (2011). Information privacy research: an interdisciplinary review. MIS Quarterly, 35(4), 989-1016.
  • Bélanger, F., & Crossler, R. E. (2011). Privacy in the digital age: a review of information privacy research in information systems. MIS Quarterly, 35(4), 1017-1042.
  • Liu, Y., Gummadi, K. P., Krishnamurthy, B., & Mislove, A. (2011, November). Analyzing facebook privacy settings: user expectations vs. reality. In Proceedings of the 2011 ACM SIGCOMM Conference on Internet Measurement Conference (pp. 61-70). ACM.
  • Malhotra, N. K., Kim, S. S., & Agarwal, J. (2004). Internet users' information privacy concerns (IUIPC): The construct, the scale, and a causal model. Information Systems Research, 15(4), 336-355.
  • Zeng, X., & Wei, L. (2013). Social ties and user content generation: Evidence from Flickr. Information Systems Research, 24(1), 71-87.
  • Smith, H. J., Milberg, S. J., & Burke, S. J. (1996). Information privacy: measuring individuals' concerns about organizational practices. MIS Quarterly, 167-196.
  • De Montjoye, Y. A., Radaelli, L., & Singh, V. K. (2015). Unique in the shopping mall: On the reidentifiability of credit card metadata. Science, 347(6221), 536-539.

Completion methods

Method 1

Select all marked parts
Parts of the completion methods
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Teaching (5 cr)

Type:
Participation in teaching
Grading scale:
0-5
Language:
English
No published teaching