HCIB 2015: HCI in Business pp 41-52 | Cite as

Privacy by Design: Examining Two Key Aspects of Social Applications

Conference paper
First Online:
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9191)

Abstract

Social applications do not only acquire users’ personal information but potentially also collects the personal information of users’ social networks. Despite considerable discussion of privacy problems in prior work, questions remain as to how to design privacy-preserving social applications and how to evaluate its effect on privacy. Drawing on the justice framework, we identify two key aspects of social, namely information acquisition and exposure control and examine the effects on user evaluation of social applications. Furthermore, we investigate the impact of this evaluation on usage intention. In doing so, we provide new insight into embedding privacy in technology development.

Keywords

Social applications Online social networks Information privacy 
This is a preview of subscription content, log in to check access.

References

  1. 1.
    Besmer, A., et al.: Social applications: exploring a more secure framework. In: Proceedings of the 5th Symposium on Usable Privacy and Security. ACM (2009)Google Scholar
  2. 2.
    Markets, R.A.: Global Online Gaming Market 2014. Research and Markets (2014)Google Scholar
  3. 3.
    Smock, A.D., et al.: Facebook as a toolkit: a users and gratification approach to unbundling feature use. Comput. Hum. Behav. 27(6), 2322–2329 (2011)CrossRefGoogle Scholar
  4. 4.
    Boyd, D.M., Ellison, N.B.: Social network sites: definition, history, and scholarship. J. Comput. Mediated Commun. 13(1), 210–230 (2007)CrossRefGoogle Scholar
  5. 5.
    Debatin, B., et al.: Facebook and online privacy: attitudes, behaviors, and unintended consequences. J. Comput. Mediated Commun. 15(1), 83–108 (2009)CrossRefGoogle Scholar
  6. 6.
    Angwin, J., Singer-Vine, J.: Selling you on facebook (2012). http://online.wsj.com/articles/SB10001424052702303302504577327744009046230
  7. 7.
    Culnan, M.J., Bies, R.J.: Consumer privacy: balancing economic and justice considerations. J. Soc. Issues 59(2), 323–342 (2003)CrossRefGoogle Scholar
  8. 8.
    Son, J.-Y., Kim, S.S.: Internet users’ information privacy-protective responses: a taxonomy and a nomological model. MIS Q. 32(3), 503–529 (2008)Google Scholar
  9. 9.
    Culnan, M.J., Armstrong, P.K.: Privacy concerns, procedural fairness, and impersonal trust: an empirical investigation. Organ. Sci. 10(1), 104–115 (1999)CrossRefGoogle Scholar
  10. 10.
    Xu, H., et al.: The role of push-pull technology in privacy calculus: the case of location-based services. J. Manag. Inf. Syst. 26(3), 135–174 (2010)CrossRefGoogle Scholar
  11. 11.
    Cropanzano, R., Ambrose, M.L.: Procedural and distributive justice are more similar than you think: a monistic perspective and a research agenda. Adv. Organ. Justice 119, 151 (2001)Google Scholar
  12. 12.
    Deutsch, M.: Equity, equality, and need: what determines which value will be used as the basis of distributive justice? J. Soc. Issues 31(3), 137–149 (1975)CrossRefGoogle Scholar
  13. 13.
    Schwinger, T.: The need principle of distributive justice. In: Bierhoff, H.W., Cohen, R.L., Greenberg, J. (eds.) Justice in Social Relations, pp. 211–225. Springer, New York (1986)CrossRefGoogle Scholar
  14. 14.
    Thibaut, J., Walker, L.: Procedural Justice: A Psychological Analysis. Erlbaum, Hillsdale (1975)Google Scholar
  15. 15.
    Wang, N., Xu, H., Grossklags, J.: Third-party apps on facebook: privacy and the illusion of control. In: CHIMIT’11 Proceedings of the 5th ACM Symposium on Computer Human Interaction for Management of Information Technology (2011)Google Scholar
  16. 16.
    Smith, H.J., Milberg, S.J., Burke, S.J.: Information privacy: Measuring individuals’ concerns about organizational practices. MIS Q. 20(2), 167–196 (1996)CrossRefGoogle Scholar
  17. 17.
    Dinev, T., Hart, P.: An extended privacy calculus model for e-commerce transactions. Inf. Syst. Res. 1(17), 2006 (2006)Google Scholar
  18. 18.
    Phelps, J., Nowak, G., Ferrell, E.: Privacy concerns and consumers willingness to provide personal information. J. Public Policy Mark. 19(1), 27–41 (2000)CrossRefGoogle Scholar
  19. 19.
    Jiang, Z., Heng, C.S., Choi, B.C.F.: Privacy concerns and privacy-protective behavior in synchronous online social interactions. Inf. Syst. Res. 24(3), 579–595 (2013)CrossRefGoogle Scholar
  20. 20.
    Malhotra, N.K., Kim, S.S., Agarwal, J.: Internet users’ information privacy concerns (IUIPC): the construct, the scale, and a causal model. Inf. Syst. Res. 15(4), 336–355 (2004)CrossRefGoogle Scholar
  21. 21.
    Lee, Y.E., Benbasat, I.: The influence of trade-off difficulty caused by preference elicitation methods on user acceptance of recommendation agents across loss and gain conditions. Inf. Syst. Res. 22(4), 867–884 (2011)CrossRefGoogle Scholar
  22. 22.
    Komiak, S.Y.X., Benbasat, I.: The effects of personalization and familiarity on trust and adoption of recommendation agents. MIS Q. 30(4), 941–960 (2006)Google Scholar
  23. 23.
    Tam, K.Y., Ho, S.Y.: Web personalization as a persuasion strategy: an elaboration likelihood model perspective. Inf. Syst. Res. 16(3), 271–291 (2005)CrossRefGoogle Scholar
  24. 24.
    Ho, S.Y., Bodoff, D., Tam, K.Y.: Timing of adaptive web personalization and its effects on online consumer behavior. Inf. Syst. Res. 22(3), 660–679 (2011)CrossRefGoogle Scholar
  25. 25.
    Hui, K.L., Teo, H.H., Lee, S.Y.T.: The value of privacy assurance: an exploratory field experiment. MIS Q. 31(1), 19–33 (2007)Google Scholar
  26. 26.
    Petronio, S.: Boundaries of Privacy: Dialectics of Disclosure. State University of New York Press, Albany (2002)Google Scholar
  27. 27.
    Awad, N.F., Krishnan, M.S.: The personalization privacy paradox: an empirical evaluation of information transparency and the willingness to be profiled online for personalization. MIS Q. 30(1), 13–28 (2006)Google Scholar
  28. 28.
    Folger, R., Konovsky, M.A.: Effects of procedural and distributive justice on reactions to pay raise decisions. Acad. Manag. J. 32(1), 115–130 (1989)CrossRefGoogle Scholar
  29. 29.
    Youn, S.: Teenagers’ perceptions of online privacy and coping behaviors: a risk-benefit appraisal approach. J. Broadcast. Electron. Media 49(1), 86–110 (2005)CrossRefGoogle Scholar
  30. 30.
    Grosser, T.J., Lopez-Kidwell, V., Labianca, G.: A social network analysis of positive and negative gossip in organizational life. Group Org. Manag. 35(2), 177–212 (2010)CrossRefGoogle Scholar
  31. 31.
    Mathieson, K.: Predicting user intentions: comparing the technology acceptance model with the theory of planned behavior. Inf. Syst. Res. 2(3), 173–191 (1991)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.School of Information Systems, Technology and Management, UNSW Australia Business SchoolUNSW AustraliaSydneyAustralia

Personalised recommendations