The DOI matches its Crossref record; 40 of the 40 references it cites were found in a registry or an index.
An Extended Privacy Calculus Model for SNSs: Analyzing Self-Disclosure and Self-Withdrawal in a Representative U.S. Sample: THE EXTENDED PRIVACY CALCULUS MODEL FOR SNSs
Open accessAbstract
The privacy calculus established that online self-disclosures are based on a cost-benefit tradeoff. For the context of SNSs, however, the privacy calculus still needs further support as most studies consist of small student samples and analyze self-disclosure only, excluding self-withdrawal (e.g., the deletion of posts), which is essential in SNS contexts. Thus, this study used a U.S. representative sample to test the privacy calculus' generalizability and extend its theoretical framework by including both self-withdrawal behaviors and privacy self-efficacy. Results confirmed the extended privacy calculus model. Moreover, both privacy concerns and privacy self-efficacy positively predicted use of self-withdrawal. With regard to predicting self-disclosure in SNSs, benefits outweighed privacy concerns; regarding self-withdrawal, privacy concerns outweighed both privacy self-efficacy and benefits.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Herne, H., Cooley, W. W., & Lohnes, P. R. (1973) · Journal of the Royal Statistical Society. Series A (General) · doi:10.2307/2344428 · Cited by 35,697
Multivariate Data Analysis, 6th ed
Tatham, R. L., Anderson, R. E., Babin, B. J., Black, W. C., & Hair, J. F. (2006) · Cited by 9,807
To parcel or not to parcel: Exploring the question, weighing the merits
Little, T. D., Cunningham, W. A., Shahar, G., & Widaman, K. F. (2002) · Structural Equation Modeling: A Multidisciplinary Journal · doi:10.1207/s15328007sem0902_1 · Cited by 6,552
I tweet honestly, I tweet passionately: Twitter users, context collapse, and the imagined audience
Marwick, A. E., & boyd, D. (2011) · New Media & Society · doi:10.1177/1461444810365313 · Cited by 4,612
Bürgel, O. (2000) · ZEW Economic Studies · doi:10.1007/978-3-642-57671-3_6 · Cited by 3,570
Internet Users' Information Privacy Concerns (IUIPC): The Construct, the Scale, and a Causal Model
Malhotra, N. K., Kim, S. S., & Agarwal, J. (2004) · Information Systems Research · doi:10.1287/isre.1040.0032 · Cited by 3,173
Rogers, R. W., & Rogers, R. W. (1983) · Medical Entomology and Zoology · Cited by 2,577
Westin, A. F. (1967) · Cited by 1,908
Information Privacy Concerns, Procedural Fairness, and Impersonal Trust: An Empirical Investigation
Culnan, M. J., & Armstrong, P. K. (1999) · Organization Science · doi:10.1287/orsc.10.1.104 · Cited by 1,870
Social psychophysiology : a sourcebook
Cacioppo, J. T., Petty, R. E., & Shapiro, D. (1983) · Cited by 1,596
Cited by
Big data analytics in E-commerce: a systematic review and agenda for future research
Akter, S., & Wamba, S. F. (2016) · Electronic Markets · doi:10.1007/s12525-016-0219-0 · Cited by 684
Antecedents and consequences of social media fatigue
Dhir, A., Kaur, P., Chen, S., & Pallesen, S. (2019) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2019.05.021 · Cited by 282
Privacy cynicism: A new approach to the privacy paradox
Hoffmann, C. P., Lutz, C., & Ranzini, G. (2016) · Cyberpsychology: Journal of Psychosocial Research on Cyberspace · doi:10.5817/cp2016-4-7 · Cited by 236
Bol, N., Dienlin, T., Kruikemeier, S., Sax, M., Boerman, S. C., Strycharz, J., Helberger, N., & de Vreese, C. H. (2018) · Journal of Computer-Mediated Communication · doi:10.1093/jcmc/zmy020 · Cited by 215
Self-citationFrom concerns to benefits: A comprehensive study of ChatGPT usage in education
Jo, H. (2024) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-024-00471-4 · Cited by 146
Metadata
- Authors
- Dienlin, T., & Metzger, M. J.
- Venue
- Journal of Computer-Mediated Communication
- Publisher
- Oxford University Press (OUP)
- Published
- 2016-08-04
- Volume
- 21
- Issue
- 5
- Pages
- 368-383
- ISSN
- 1083-6101 (ISSN-L)
- OpenAlex
- W2503866476
- Cited by
- 391
- References
- 40
- FWCI
- 70.50
- Type
- journal article
- Language
- en
- Open access
- bronze
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: An Extended Privacy Calculus Model for SNSs: Analyzing Self-Disclosure and Self-Withdrawal in a Representative U.S. Sample: THE EXTENDED PRIVACY CALCULUS MODEL FOR SNSs. https://app.cochat.ai/papers/10.1111/jcc4.12163
- The paper
- Dienlin, T., & Metzger, M. J. (2016). An Extended Privacy Calculus Model for SNSs: Analyzing Self-Disclosure and Self-Withdrawal in a Representative U.S. Sample: THE EXTENDED PRIVACY CALCULUS MODEL FOR SNSs. Journal of Computer-Mediated Communication. https://doi.org/10.1111/jcc4.12163
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
