Total views : 334

A Study of Factors that Affect the Right to be Forgotten and Self-Disclosure Intent in SNS


  • Center for Free Semester and Career Experience Program, Korea Research Institute for Vocational Education and Training, Republic of Korea
  • Department of Management Information Systems, Chungbuk National University, Republic of Korea
  • Department of Policy Research, Korea Institute of Science and Technology Information, Republic of Korea


Background/Objectives: We wanted to find out the relationship between self-disclosure intent to disclose themselves online openly and the right to be forgotten that they want their information to be forgotten online. Methods/Statistical Analysis: In order to measure each variable of the research model, all items of the questionnaire were measured with fivepoint Likert scale. Questionnaire items were modified according to the environment called social network service from existing studies. Also, verification for the measurement model was carried out targeting a total of 115 responses used in the analysis. For measurement model verification, we used Partial Least Square, a structural equation approach and used SmartPLS 2.0. Findings: According to the study results, perceived privacy risk had a significant effect both on privacy protection awareness and privacy concern. Perceived privacy can be understood to affect acceptance of the right to be forgotten by a medium of privacy protection awareness and privacy concern because the path known for privacy protection awareness and privacy concern to affect acceptance of the right to be forgotten was also found to be significant. On the other hand, the hypothesis that privacy self-efficacy affects privacy protection awareness and the hypothesis that privacy concern and acceptance of the right to be forgotten have a significant effect on self-disclosure intent were rejected. In order to use SNS, some degree of personal information disclosure is inevitable. Therefore, feeling concerned about privacy or not does not have any effect on self-disclosure intent in SNS. Likewise, the relationship between acceptance of the right to be forgotten and self-disclosure intent also turned out not to be related each other. Application/Improvements: Protection Motivation Theory should be applied as the antecedent of privacy protection awareness or in-depth research on other privacy-related factors affecting self-disclosure intent in addition to self-presentation needs.


Partial Least Square, Privacy Self-Disclosure, Social Network Services, The Right to be Forgotten

Full Text:

 |  (PDF views: 288)


  • Kim HI. Legalization of right to be forgotten and freedom of press in the digital media environment. Journal of Digital Convergence. 2013; 11(9):21–7.
  • Invasion of privacy or the right to be informed? A fierce controversy of the right to be forgotten. Available from:
  • Could the ‘right to be forgotten’ become automated? Oblivion software could help Google remove hundreds of people from the web in seconds. Available from:
  • Hong MS. A review- Delete: The virtue of forgetting in the digital age. Review of Culture and Economy. 2011; 14(2):139–46.
  • Kang SR. A review on the right to be forgotten online. Journal of Small and Medium Business Law. 2012; 3(2):9–36.
  • Ku YC, Chen R, Zhang H. Why do users continue using social networking sites? An exploratory study of members in the United States and Taiwan. Information and Management.2013; 50(7):571–81.
  • Kwak KT, Choi SK, Lee BG. SNS flow, SNS self-disclosure and post hoc interpersonal relations change: Focused on Korean Facebook user. Computers in Human Behavior.2014; 31(1):294–304.
  • Lee JH, Yu SY. The mediating effect of the flow experience: Causal model analysis on the effect of users’ awareness of SNS characteristics on the acceptance of SNS. Indian Journal of Science and Technology. 2015; 8(8):258–66.
  • Kim JY, Chung N, Ahn KM. Why people use social networking services in Korea the mediating role of self-disclosure on subjective well-being. Information Development.2014; 30(3):276–87.
  • Java A, Song X, Finin T, Tseng B. Why we twitter: An analysis of a microblogging community. In Advances in Web Mining and Web Usage Analysis. Springer Berlin Heidelberg.2009; 5439:118–38.
  • Tuunainen VK, Pitkanen O, Hovi M. Users’ awareness of privacy on online social networking sites-Case Facebook.22nd Bled eConference 2009 Proceedings; Slovenia. 2009.
  • p. 1–16.12. Chang CW, Heo J. Visiting theories that predict college students’ self-disclosure on Facebook. Computers in Human Behavior. 2014; 30(1):79–86.
  • Salleh N, Aditiawarman U, Hussein R. Information disclosure behaviour in social media among Malaysian youth: The impact of privacy concern, risk and trust. Symposium on Information and Computer Sciences Malaysia; 2011. p.1–4.
  • Puri GD, Haritha D. Survey big data analytics, applications and privacy concerns. Indian Journal of Science and Technology.2016; 9(17):1–8.
  • Wheeless LR, Grotz J. Conceptualization and measurement of reported self-disclosure. Human Communication Research.1976; 2(4):338–46.
  • Greene K, Derlega VJ, Mathews A. Self-disclosure in personal relationships. The Cambridge Handbook of Personal Relationships; 2006. p. 409–27.
  • Altman I, Taylor DA, Rinehart R, Winston NY. Social penetration: The development of interpersonal relationships; 1973.
  • Rui J, Stefanone MA. Strategic self-presentation online: A cross-cultural study. Computers in Human Behavior. 2013; 29(1):110–8.
  • Xu F, Michael K, Chen X. Factors affecting privacy disclosure on social network sites: An integrated model. Electronic Commerce Research. 2013; 13(2):151–68.
  • Park N, Jin B, Jin SAA. Effects of self-disclosure on relational intimacy in Facebook. Computers in Human Behavior.2011; 27(5):1974–83.
  • Chen X, Pan Y, Cai S. User self-disclosure on SNSs: A privacy risk and social capital perspective. In Proceedings of the 13th International Conference on Electronic Business; Singapore. 2013. p. 207–16.
  • Dwyer C, Hiltz S, Passerini K. Trust and privacy concern within social networking sites: A comparison of Facebook and MySpace. Americas Conference on Information Systems Proceedings; USA. 2007.
  • Ozer EM, Bandura A. Mechanisms governing empowerment effects: A self-efficacy analysis. Journal of Personality and Social Psychology. 1990; 58(3):472–86.
  • Rhee HS, Kim C, Ryu YU. Self-efficacy in information security: Its influence on end users’ information security practice behavior. Computers and Security. 2009; 28(8):816–26.
  • Jang SH, Lee KD. Privacy risk of social network service and user resistance. The e-business Studies. 2014; 15(3):323–38.
  • Kim SH, Park HS. An analysis of influence factors on privacy protection awareness and protection behavior and moderating effect of privacy invasion experience. The Journal of Internet Electronic Commerce Research. 2013; 13(4):79–105.
  • Zhou T, Li H. Understanding mobile SNS continuance usage in China from the perspectives of social influence and privacy concern. Computers in Human Behavior. 2014; 37(1):283–9.
  • Xu H, Dinev T, Smith HJ, Hart P. Examining the formation of individual’s privacy concerns: Toward an integrative view. International Conference on Information Systems Proceedings; France. 2008. p. 1–16.
  • Almadhoun NM, Dominic P, Woon LF. Perceived security, privacy, and trust concerns within social networking sites: The role of information sharing and relationships development in the Malaysian higher education institutions’ marketing. In IEEE International Conference on Control System, Computing and Engineering; Malaysia. 2011. p.426–31.
  • Lin SW, Liu YC. The effects of motivations, trust, and privacy concern in social networking. Service Business. 2012; 6(4):411–24.
  • Lo J, Riemenschneider CK. An examination of privacy concerns and trust entities in determining willingness to disclose personal information on a social networking site.Americas Conference on Information Systems Proceedings; Peru. 2010. p. 1–11.
  • Krasnova H, Kolesnikova E, Guenther O. It won’t happen to me!: Self-disclosure in online social networks. Americas Conference on Information Systems 2009 Proceedings; USA. 2009. p. 1–9.
  • Lee SB, Fan L, Lee SC, Suh YH. Effects of self-presentation and privacy concern on an individual’s self-disclosure: An empirical study on Twitter. Korean Management Science Review. 2012; 29(2);1–20.
  • Apply PLS-SEM Method in Minutes. With No Headaches!Available from:
  • Fornell C, Larcker D. Evaluating structural equation models with unobservable variables and measurement error.Journal of Marketing Research. 1981; 18(1):39–50.
  • Nunnally JC. Psychometric theory. NY: McGrow-Hill.1987; 17(1):1–6.
  • Thompson R, Barclay DW, Higgins CA. The Partial Least Squares (PLS) approach to causal modeling: Personal computer adoption and use as an illustration. Technology Studies: Special Issue on Research Methodology. 1995; 2(2):284–324.
  • Chin WW. The partial least squares approach to structural equation modeling. Modern Methods for Business Research.1998; 295–336.
  • Falk RF, Miller NB. A primer for soft modeling. Ohio: University of Akron Press; 1992. p. 103.
  • Jin H, Park ST, Li G. Factors influencing customer paticipation in mobile SNS: Focusing on wechat in China. Indian Journal of Science and Technology. 2015 Oct; 8(26):1–8.
  • Park EM, Park ST. The effectiveness of absorptive capacity formation mechanism on innovation performance by industry. Indian Journal of Science and Technology. 2015 Sep; 8(21):1–9.


  • There are currently no refbacks.

Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.