Privacy-awareness information for web forums: results from an empirical study
Abstract
While interacting with others on the internet, users share a lot of personal data with a potentially large but "invisible" audience. An important issue is maintaining control over personal data and therefore, in the first place, users need to be aware to whom they are disclosing which data. Based on the cues-filtered-out theory we introduce a new feature to support the privacy-awareness of forum users and tested it with 313 users. The results of our empirical study show that the presentation of privacy-related context cues indeed increases forum users' privacy-awareness. This is an important precondition for users' willingness to modify privacy settings or to use privacy-enhancing technologies.
Integrity 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?
Cues-Filtered-Out Theory implies that individuals disclose more personal data in computer-mediated communication settings compared to face-to-face settings due to the absence of social and contextual cues leading to disclosure of information online despite general privacy concerns.
“Cues-Filtered-Out Theory (Sproull andKiesler, 1986, 1991) implies that individuals disclose more personal data in computermediated communication settings compared to face-to-face settings due to the absence of social and contextual cues leading to disclosure of information online despite general privacy concerns (Pötzsch et al., 2010).”
From The privacy paradox – investigating discrepancies between expressed privacy concerns and actual online behavior – a systematic literature review (2017) · cites this paper as Pötzsch et al., 2010
Cites
Tversky, A., & Kahneman, D. (1974) · Science · doi:10.1126/science.185.4157.1124 · Cited by 28,810 · see citing works
Information revelation and privacy in online social networks
Gross, R., & Acquisti, A. (2005) · Proceedings of the 2005 ACM workshop on Privacy in the electronic society · doi:10.1145/1102199.1102214 · Cited by 2,028 · see citing works
Imagined Communities: Awareness, Information Sharing, and Privacy on the Facebook
Acquisti, A., & Gross, R. (2006) · Lecture Notes in Computer Science · doi:10.1007/11957454_3 · Cited by 1,895 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Barth, S., & de Jong, M. D. T. (2017) · Telematics and Informatics · doi:10.1016/j.tele.2017.04.013 · Cited by 798 · see citing works
“Privacy awareness tools should empower users to make well-informed decisions with regard to their information disclosure (Pötzsch et al., 2010).”
Background
- Authors
- Pötzsch, S., Wolkerstorfer, P., & Graf, C.
- Affiliations
- Technische Universität Dresden (DE)
- Center for Usability Research and Engineering (AT)
- Venue
- Proceedings of the 6th Nordic Conference on Human-Computer Interaction: Extending Boundaries
- Publisher
- ACM
- Published
- 2010-10-16
- Pages
- 363-372
- OpenAlex
- W1991691282
- Cited by
- 13
- References
- 3
- Citations by year
- 2025: 2 · 2023: 1 · 2021: 3 · 2020: 1 · 2019: 1 · 2017: 1 · 2014: 1 · 2013: 2
- FWCI
- 2.80
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- Nordic Conference on Human-Computer Interaction (publishedVersion)
- Funders
- Seventh Framework Programme (216483)
- Topics
- Social Sciences › Sociology and Political Science › Privacy, Security, and Data Protection
- Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
- Physical Sciences › Computer Science › Artificial Intelligence › Privacy-Preserving Technologies in Data
- Keywords
- privacy awareness, online forums, contextual cues, personal information disclosure, privacy settings, privacy-enhancing technologies, user privacy control
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