Privacy concerns and benefits of engagement with social media-enabled apps: A privacy calculus perspective
Open accessIntegrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The subjective nature of privacy issues, the widespread expansion of online platforms, multi-party participation, the nature of data disclosure, and associated ethics make determining the contradictory effects between personal privacy issues and behavior challenging.
“The subjective nature of privacy issues, the widespread expansion of online platforms, multi-party participation, the nature of data disclosure, and associated ethics make determining the contradictory effects between personal privacy issues and behavior challenging [106,107].”
From What Influences Users’ Intention to Share Works in Designer-Driven User-Generated Content Communities? A Study Based on Self-Determination Theory (2023) · cites this paper as [106]
No citation lists for this paper
No citation lists for this paper yet — checked again daily.
References 102 · Cited by 303
- Authors
- Jozani, M., Ayaburi, E., Ko, M., & Choo, K.-K. R.
- Affiliations
- The University of Texas at San Antonio (US)
- The University of Texas Rio Grande Valley (US)
- Corresponding author
- Choo, Kim-Kwang Raymond
- Venue
- Computers in Human Behavior
- Publisher
- Elsevier BV
- Published
- 2020-06
- Volume
- 107
- Pages
- 106260
- ISSN
- 0747-5632 (ISSN-L)
- OpenAlex
- W3003129027
- Cited by
- 303
- References
- 102
- Citations by year
- 2026: 44 · 2025: 56 · 2024: 60 · 2023: 57 · 2022: 47 · 2021: 31 · 2020: 8
- FWCI
- 44.47
- Type
- journal article
- Language
- en
- Open access
- Licence
- Locations
- Computers in Human Behavior (publishedVersion)
- ScholarWorks @ UTRGV (The University of Texas Rio Grande Valley) (submittedVersion, cc-by-nc-nd)
- Topics
- Social Sciences › Sociology and Political Science › Privacy, Security, and Data Protection
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Physical Sciences › Computer Science › Artificial Intelligence › Privacy-Preserving Technologies in Data
- Keywords
- privacy calculus, user engagement, mobile application
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
