research-article

Applying Protection Motivation Theory to Predict Facebook Users’ Withdrawal and Disclosure Intentions

Authors:

Johanna Schäwel,

Nicole C. KrämerAuthors Info & Claims

SMSociety'20: International Conference on Social Media and Society

Pages 21 - 29

https://doi.org/10.1145/3400806.3400810

Published: 22 July 2020 Publication History

Abstract

Because legislation only slowly finds ways to better protect Internet users’ privacy and is heavily country-dependent, self-data protection is of major importance. The current investigation applies the protection motivation theory to investigate factors that predict Facebook users’ privacy protection motivation and to examine whether fear appeals and social norms can raise participants’ intention to protect personal data. In a 2 (warning vs. neutral message) x 3 (high vs. low norms vs. control) online experiment (N = 304), participants were told they would receive a personalized privacy protection recommendation based on their Facebook profile's privacy settings. Whereas neither the fear appeal nor high social norms led to an increase in privacy protection motivation, analyses revealed that privacy threat perception and the perceived effectiveness of privacy protection are important factors for explaining self-withdrawal intention among Facebook users.

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Zhang DStrycharz JBoerman SAraujo TVoorveld H(2025)Google knows me too well! Coping with perceived surveillance in an algorithmic profiling contextComputers in Human Behavior10.1016/j.chb.2024.108536165(108536)Online publication date: Apr-2025
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Johannes Wilke AMagnus Nold JBraun OMeissner FGroße-Kampmann M(2024)Self-promotion with a chance of warnings: Exploring Cybersecurity Communication Among Government Institutions on LinkedInProceedings of the International Conference on Mobile and Ubiquitous Multimedia10.1145/3701571.3701575(119-132)Online publication date: 1-Dec-2024
https://dl.acm.org/doi/10.1145/3701571.3701575
Meier YKrämer N(2024)Differences in access to privacy information can partly explain digital inequalities in privacy literacy and self-efficacyBehaviour & Information Technology10.1080/0144929X.2024.2349183(1-16)Online publication date: 3-May-2024
https://doi.org/10.1080/0144929X.2024.2349183
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Applying Protection Motivation Theory to Predict Facebook Users’ Withdrawal and Disclosure Intentions
1. Security and privacy
2. Social and professional topics
  1. Computing / technology policy

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cover image ACM Other conferences

SMSociety'20: International Conference on Social Media and Society

July 2020

317 pages

ISBN:9781450376884

DOI:10.1145/3400806

Editors:
Anatoliy Gruzd
Ryerson University in Canada
,
Philip Mai
Ryerson University in Canada
,
Raquel Recuero
Federal University of Pelotas and Federal University of Rio Grande do Sul in Brazil
,
Ángel Hernández-García
Universidad Politécnica de Madrid in Spain
,
Chei Sian Lee
Nanyang Technological University in Singapore
,
James Cook
University of Maine at Augusta in the United States
,
Jaigris Hodson
Royal Roads University in Canada
,
Bree McEwan
DePaul University in the United States
,
Jill Hopke
DePaul University in the United States

Copyright © 2020 ACM.

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Published: 22 July 2020

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SMSociety'20

SMSociety'20: International Conference on Social Media and Society

July 22 - 24, 2020

ON, Toronto, Canada

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Cited By

Zhang DStrycharz JBoerman SAraujo TVoorveld H(2025)Google knows me too well! Coping with perceived surveillance in an algorithmic profiling contextComputers in Human Behavior10.1016/j.chb.2024.108536165(108536)Online publication date: Apr-2025
https://doi.org/10.1016/j.chb.2024.108536
Johannes Wilke AMagnus Nold JBraun OMeissner FGroße-Kampmann M(2024)Self-promotion with a chance of warnings: Exploring Cybersecurity Communication Among Government Institutions on LinkedInProceedings of the International Conference on Mobile and Ubiquitous Multimedia10.1145/3701571.3701575(119-132)Online publication date: 1-Dec-2024
https://dl.acm.org/doi/10.1145/3701571.3701575
Meier YKrämer N(2024)Differences in access to privacy information can partly explain digital inequalities in privacy literacy and self-efficacyBehaviour & Information Technology10.1080/0144929X.2024.2349183(1-16)Online publication date: 3-May-2024
https://doi.org/10.1080/0144929X.2024.2349183
Freye MBuchner B(2024)Digitale Gesundheitstechnologien – das Recht als Hemmschuh oder Wegbereiter?Legal regulation of digital public health interventions—hindrance or stimulus?Bundesgesundheitsblatt - Gesundheitsforschung - Gesundheitsschutz10.1007/s00103-024-03835-3Online publication date: 8-Feb-2024
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Meier YKrämer N(2023)A longitudinal examination of Internet users’ privacy protection behaviors in relation to their perceived collective value of privacy and individual privacy concernsNew Media & Society10.1177/1461444822114279926:10(5942-5961)Online publication date: 5-Jan-2023
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