Becoming a professional influencer on LinkedIn: Privacy calculus drivers of self-disclosure

Jorge Serrano-Malebrán 1 * , Carlos Molina 2, Jesús Yeves 3 4
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1 Facultad de Ingeniería y Negocios, Escuela de Administración y Negocios, Universidad de las Americas, Santiago, CHILE
2 Facultad de Economía y Administración, Centro de Emprendimiento y de la Pyme, Universidad Católica del Norte, Antofagasta, CHILE
3 Programa de Estudios Psicosociales del Trabajo (PEPET), Facultad de Psicología, Universidad Diego Portales, Santiago, CHILE
4 Núcleo Milenio sobre la Evolución del Trabajo (MNEW), Santiago, CHILE
* Corresponding Author
Online Journal of Communication and Media Technologies, Volume 16, Issue 4, Article No: e202652. https://doi.org/10.30935/ojcmt/19273
OPEN ACCESS   18 Views   10 Downloads   Published online: 17 Sep 2026
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ABSTRACT

This study examines the factors that influence users’ self-disclosure on LinkedIn through the lens of privacy calculus theory, considering perceived benefits, trust, and privacy concerns. A survey of 370 active users in Chile was conducted, and a structural model was assessed using partial least squares structural equation modeling. The results show that self-disclosure is primarily driven by functional and symbolic benefits, particularly learning/information exchange and professional self-presentation. Trust in the platform positively affects the willingness to disclose and reduces privacy concerns. In contrast, trust in other members, privacy concerns, and benefits related to professional networking and career development did not have significant effects. These findings suggest that in Latin American professional contexts, self-disclosure is more aligned with visibility and positioning oriented strategies than with explicit job search intentions. This study offers theoretical implications by extending privacy calculus to professional networking platforms and practical implications for platform design and recruitment strategies that rely more on reputational signals than on active job-seeking behaviors.

CITATION

Serrano-Malebrán, J., Molina, C., & Yeves, J. (2026). Becoming a professional influencer on LinkedIn: Privacy calculus drivers of self-disclosure. Online Journal of Communication and Media Technologies, 16(4), e202652. https://doi.org/10.30935/ojcmt/19273

REFERENCES

  • Acquisti, A., Brandimarte, L., & Loewenstein, G. (2015). Privacy and human behavior in the age of information. Science, 347(6221), 509-514. https://doi.org/10.1126/science.aaa1465
  • Barta, K., & Andalibi, N. (2024). Theorizing self visibility on social media: A visibility objects lens. ACM Transactions on Computer-Human Interaction, 31(3), Article 31. https://doi.org/10.1145/3660337
  • Caers, R., & Castelyns, V. (2011). Linkedin and Facebook in Belgium: The influences and biases of social network sites in recruitment and selection procedures. Social Science Computer Review, 29(4), 437-448. https://doi.org/10.1177/0894439310386567
  • Chang, S. E., Liu, A. Y., & Shen, W. C. (2017). User trust in social networking services: A comparison of Facebook and LinkedIn. Computers in Human Behavior, 69, 207-217. https://doi.org/10.1016/j.chb.2016.12.013
  • Cheung, C., Lee, Z. W. Y., & Chan, T. K. H. (2015). Self-disclosure in social networking sites the role of perceived cost, perceived benefits and social influence. Internet Research, 25(2), 279-299. https://doi.org/10.1108/IntR-09-2013-0192
  • Choi, Y. H., & Bazarova, N. N. (2015). Self-disclosure characteristics and motivations in social media: Extending the functional model to multiple social network sites. Human Communication Research, 41(4), 480-500. https://doi.org/10.1111/hcre.12053
  • Column. (2025). LinkedIn statistics: 2025 shocking facts you need to know. Column Content. https://columncontent.com/linkedin-statistics/
  • Dinev, T., & Hart, P. (2006). An extended privacy calculus model for e-commerce transactions. Information Systems Research, 17(1), 61-80. https://doi.org/10.1287/isre.1060.0080
  • Eitiveni, I., Hidayanto, A. N., Dwityafani, Y. A., & Kumaralalita, L. (2023). Self-disclosure on professional social networking sites: A privacy calculus perspective. Human Behavior and Emerging Technologies. https://doi.org/10.1155/2023/2643683
  • Florenthal, B. (2015). Applying uses and gratifications theory to students’ LinkedIn usage. Young Consumers, 16(1), 17-35. https://doi.org/10.1108/YC-12-2013-00416
  • Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50. https://doi.org/10.2307/3151312
  • Grissa, K. (2017). What “uses and gratifications” theory can tell us about using professional networking sites (e.g., Linkedin, Viadeo, Xing, Skilledafricans, Plaxo …). In R. Jallouli, O. Zaïane, M. Bach Tobji, R. Srarfi Tabbane, & A. Nijholt (Eds.), Digital economy. Emerging technologies and business innovation. ICDEc 2017. Lecture notes in business information processing, vol 290 (pp. 15-28). Springer. https://doi.org/10.1007/978-3-319-62737-3_2
  • Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2022). A primer on partial least squares structural equation modeling (PLS-SEM). SAGE.
  • Henseler, J., Hubona, G., & Ray, P. A. (2016). Using PLS path modeling in new technology research: Updated guidelines. Industrial Management & Data Systems, 116(1), 2-20. https://doi.org/10.1108/IMDS-09-2015-0382
  • Hofstetter, R., Rüppell, R., & John, L. K. (2017). Temporary sharing prompts unrestrained disclosures that leave lasting negative impressions. PNAS, 114(45), 11902-11907. https://doi.org/10.1073/pnas.1706913114
  • Hossain, M. A. (2019). Effects of uses and gratifications on social media use: The Facebook case with multiple mediator analysis. PSU Research Review, 3(1), 16-28. https://doi.org/10.1108/PRR-07-2018-0023
  • Jain, A. K., Sahoo, S. R., & Kaubiyal, J. (2021). Online social networks security and privacy: Comprehensive review and analysis. Complex and Intelligent Systems, 7(5), 2157-2177. https://doi.org/10.1007/s40747-021-00409-7
  • Joinson, A. N., & Paine, C. B. (2007). Self-disclosure, privacy and the Internet. In Oxford Handbook of Internet psychology (pp. 237-252). Oxford University Press. https://doi.org/10.1093/oxfordhb/9780199561803.013.0016
  • Jozani, M., Ayaburi, E., Ko, M., & Choo, K. K. R. (2020). Privacy concerns and benefits of engagement with social media-enabled apps: A privacy calculus perspective. Computers in Human Behavior, 107, Article 106260. https://doi.org/10.1016/j.chb.2020.106260
  • Kaun, A. (2014). Jose van Dijck: Culture of connectivity: A critical history of social media. Oxford: Oxford University Press. 2013. MedieKultur: Journal of Media and Communication Research, 30(56). https://doi.org/10.7146/mediekultur.v30i56.16314
  • Kim, B. (2018). Understanding the role of conscious and automatic mechanisms in social networking services: A longitudinal study. International Journal of Human-Computer Interaction, 34(9), 805-818. https://doi.org/10.1080/10447318.2017.1392079
  • Krasnova, H., Spiekermann, S., Koroleva, K., & Hildebrand, T. (2010). Online social networks: Why we disclose. Journal of Information Technology, 25(2), 109-125. https://doi.org/10.1057/jit.2010.6
  • LinkedIn. (2025). LinkedIn privacy policy. LinkedIn. https://www.linkedin.com/legal/privacy-policy
  • Liu, C., Ang, R. P., & Lwin, M. O. (2013). Cognitive, personality, and social factors associated with adolescents’ online personal information disclosure. Journal of Adolescence, 36(4), 629-638. https://doi.org/10.1016/j.adolescence.2013.03.016
  • Marin, L. (2021). Sharing (mis)information on social networking sites. An exploration of the norms for distributing content authored by others. Ethics and Information Technology, 23(3), 363-372. https://doi.org/10.1007/s10676-021-09578-y
  • McKnight, D. H., Choudhury, V., & Kacmar, C. (2002). Developing and validating trust measures for e-commerce: An integrative typology. Information Systems Research, 13(3), 334-359. https://doi.org/10.1287/isre.13.3.334.81
  • Min, J., & Kim, B. (2015). How are people enticed to disclose personal information despite privacy concerns in social network sites? the calculus between benefit and cost. Journal of the Association for Information Science and Technology, 66(4), 839-857. https://doi.org/10.1002/asi.23206
  • Monteith, S., & Glenn, T. (2016). Automated decision-making and big data: Concerns for people with mental illness. Current Psychiatry Reports, 18, Article 112. https://doi.org/10.1007/s11920-016-0746-6
  • Mutimukwe, C., Kolkowska, E., & Grönlund, Å. (2020). Information privacy in e-service: Effect of organizational privacy assurances on individual privacy concerns, perceptions, trust and self-disclosure behavior. Government Information Quarterly, 37(1), Article 101413. https://doi.org/10.1016/j.giq.2019.101413
  • Oghazi, P., Schultheiss, R., Chirumalla, K., Kalmer, N. P., & Rad, F. F. (2020). User self-disclosure on social network sites: A cross-cultural study on Facebook’s privacy concepts. Journal of Business Research, 112, 531-540. https://doi.org/10.1016/j.jbusres.2019.12.006
  • Ringle, C. M., Wende, S., & Becker, J.-M. (2022). SmartPLS 4. SmartPLS. https://www.smartpls.com/
  • Sameen, S., & Cornelius, S. (2013). Social networking sites and hiring: How social media profiles influence hiring decisions. Journal of Business Studies Quarterly, 7(1), .
  • Supergrow. (2025). What is LinkedIn creator mode and how to leverage it effectively? Supergrow. https://www.supergrow.ai/blog/what-is-linkedin-creator-mode?utm_source=chatgpt.com
  • Tagembed. (2025). Top LinkedIn statistics to drive engagement & growth in 2025. Tagembed. https://tagembed.com/blog/linkedin-statistics/
  • Trepte, S., Scharkow, M., & Dienlin, T. (2020). The privacy calculus contextualized: The influence of affordances. Computers in Human Behavior, 104, Article 106115. https://doi.org/10.1016/j.chb.2019.08.022
  • van der Schyff, K., & Flowerday, S. (2023). The mediating role of perceived risks and benefits when self-disclosing: A study of social media trust and FoMO. Computers and Security, 126, Article 103071. https://doi.org/10.1016/j.cose.2022.103071
  • Voorhees, C. M., Brady, M. K., Calantone, R., & Ramirez, E. (2016). Discriminant validity testing in marketing: An analysis, causes for concern, and proposed remedies. Journal of the Academy of Marketing Science, 44(1), 119-134. https://doi.org/10.1007/s11747-015-0455-4
  • Wang, T., Duong, T. D., & Chen, C. C. (2016). Intention to disclose personal information via mobile applications: A privacy calculus perspective. International Journal of Information Management, 36(4), 531-542. https://doi.org/10.1016/j.ijinfomgt.2016.03.003
  • Waterloo, S. F., Baumgartner, S. E., Peter, J., & Valkenburg, P. M. (2018). Norms of online expressions of emotion: Comparing Facebook, Twitter, Instagram, and WhatsApp. New Media and Society, 20(5), 1813-1831. https://doi.org/10.1177/1461444817707349
  • Weiss, J., & Glück, A. (2024). “The LinkedIn self”: How personality influences self-presentations of LinkedIn users. Journal of Promotional Communications, 10(1).
  • Yao, Y., Taylor, S. H., & Leiser Ransom, S. (2024). Who’s viewing my post? Extending the imagined audience process model toward affordances and self-disclosure goals on social media. Social Media and Society, 10(1). https://doi.org/10.1177/20563051231224271
  • Zhang, F., Kothari, M., & Tiwana, B. (2024). Leveraging dwell time to improve member experiences on the LinkedIn feed. LinkedIn. https://www.linkedin.com/blog/engineering/feed/leveraging-dwell-time-to-improve-member-experiences-on-the-linkedin-feed
  • Zhao, L., Lu, Y., & Gupta, S. (2012). Disclosure intention of location-related information in location-based social network services. International Journal of Electronic Commerce, 16(4), 53-90. https://doi.org/10.2753/JEC1086-4415160403
  • Zlatolas, L. N., Welzer, T., Heričko, M., & Hölbl, M. (2015). Privacy antecedents for SNS self-disclosure: The case of Facebook. Computers in Human Behavior, 45, 158-167. https://doi.org/10.1016/j.chb.2014.12.012