Please use this identifier to cite or link to this item:
https://hdl.handle.net/10356/76575
Title: | Using fear appeals to promote data protection on social media | Authors: | Kesuma Kwee, Erika Amelia Chan, Faith Lee, Pei Shan Tan, Jaz-Ley |
Keywords: | DRNTU::Social sciences::Mass media::Media law, ethics and policy DRNTU::Humanities::Ethics |
Issue Date: | 2019 | Abstract: | As social media use has increased immensely, digital data privacy has become a serious concern in a digitally-savvy society like Singapore. In this study, an online experiment was conducted to investigate how fear appeals work in promoting the adoption of data protection behaviour on social media using the Extended Parallel Process Model (EPPM). Privacy concern was introduced into the model as a variable specific to the context of data privacy. Results suggest that privacy concern is elicited by perceived threat but not perceived efficacy, and affects one’s intention to adopt adaptive behaviour. Contrary to findings from other papers, the current study found that perceived threat and perceived efficacy operate independently in leading to behavioural intention. This offers an alternative to the typical threat-centric fear appeals, where messages can be crafted to encourage prosocial and proactive behaviours as opposed to reactive behaviours, in encouraging adaptive behaviour on social media. The study offers new insights and practical implications in assisting the presentation of messages that help increase privacy concern and data privacy protection behaviour on social media. | URI: | http://hdl.handle.net/10356/76575 | Schools: | Wee Kim Wee School of Communication and Information | Organisations: | Info-communications Media Development Authority | Rights: | Nanyang Technological University | Fulltext Permission: | restricted | Fulltext Availability: | With Fulltext |
Appears in Collections: | WKWSCI Student Reports (FYP/IA/PA/PI/CA) |
Files in This Item:
File | Description | Size | Format | |
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SCI18019.pdf Restricted Access | Research Paper | 1.11 MB | Adobe PDF | View/Open |
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