Imagined Communities: Awareness, Information Sharing, and Privacy on the Facebook
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Privacy concerns may affect what users do or share online.
“Besides self-presentation, privacy concerns may also affect what users do or share online”
From Social Data: Biases, Methodological Pitfalls, and Ethical Boundaries (2019) · cites this paper as Acquisti and Gross, 2006
If emails feel invasive, customer trust can drop, and poor data practices can harm a brand's reputation, making transparency in data usage essential for long-term success.
“Privacy concerns also play significant role; if emails feel invasive, customer trust can drop and poor data practices can harm brand's reputation, making transparency in data usage essential for long-term success (Acquisti & Gross, 2006;Martin et al., 2017).”
From Feeling Watched: A Phenomenological Exploration of Consumer Discomfort and Data Privacy Concerns in E-Commerce Personalized Email Marketing (2025) · cites this paper as Acquisti & Gross, 2006
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- Authors
- Acquisti, A., & Gross, R.
- ORCID
- Acquisti, Alessandro
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer Berlin Heidelberg
- Published
- 2006
- Pages
- 36-58
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W2150045067
- Cited by
- 1,895
- References
- 12
- Citations by year
- 2026: 20 · 2025: 35 · 2024: 46 · 2023: 50 · 2022: 76 · 2021: 85 · 2020: 86 · 2019: 94 · 2018: 118 · 2017: 99 · 2016: 131 · 2015: 138 · 2014: 177 · 2013: 179 · 2012: 177
- FWCI
- 108.08
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- Lecture notes in computer science (publishedVersion)
- 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
- Facebook, social networking sites, privacy concerns, information sharing, privacy awareness, self-disclosure, network membership, university students
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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.
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