The Effect of Privacy Concerns, Interaction, Trust, Age, and Gender on Self-Disclosure Behaviours on Social Networking Sites
Authors: Coca, A., Li, F., Shiaeles, S., Wu, D. and Liu, F.
Journal: Proceedings of the 2024 IEEE International Conference on Cyber Security and Resilience, CSR 2024
Pages: 551-556
DOI: 10.1109/CSR61664.2024.10679350
Abstract:Social networking sites (SNSs) are typically associated with positives such as making friends, they also function on a model that involves a security-threating behaviour called user self-disclosure. Despite numerous efforts to understand the motivation behind self-disclosure on social networking websites, factors influencing this phenomenon are still not fully understood. The data for this study was collected through an online questionnaire that was completed by 95 participants. Results from Spearman's correlation, One-way ANOVA, and Student's t-test suggest that privacy concerns, interaction, social trust, trust in the social networking site provider, and gender are significant in predicting self-disclosure on SNSs. The results also show no significant differences in selfdisclosure between different age groups, suggesting age as not being a predictor.
https://eprints.bournemouth.ac.uk/40317/
Source: Scopus
The effect of privacy concerns, interaction, trust, age, and gender on self-disclosure behaviours on social networking sites
Authors: Coca, A., Li, F., Shiaeles, S., Wu, D. and Liu, F.
Journal: 2024 IEEE INTERNATIONAL CONFERENCE ON CYBER SECURITY AND RESILIENCE, CSR
Pages: 551-556
DOI: 10.1109/CSR61664.2024.10679350
https://eprints.bournemouth.ac.uk/40317/
Source: Web of Science (Lite)
The effect of privacy concerns, interaction, trust, age, and gender on self-disclosure behaviours on social networking sites
Authors: Coca, A., Li, F., Shiaeles, S., Wu, D. and Liu, F.
Conference: IEEE International Conference on Cyber Security and Resilience
Dates: 2-4 September 2024
Abstract:Social networking sites (SNSs) are typically associated with positives such as making friends, they also function on a model that involves a security-threating behaviour called user self-disclosure. Despite numerous efforts to understand the motivation behind self-disclosure on social networking websites, factors influencing this phenomenon are still not fully understood. The data for this study was collected through an online questionnaire that was completed by 95 participants. Results from Spearman’s correlation, One-way ANOVA, and Student’s t-test suggest that privacy concerns, interaction, social trust, trust in the social networking site provider, and gender are significant in predicting self-disclosure on SNSs. The results also show no significant differences in self-disclosure between different age groups, suggesting age as not being a predictor.
https://eprints.bournemouth.ac.uk/40317/
Source: Manual
The effect of privacy concerns, interaction, trust, age, and gender on self-disclosure behaviours on social networking sites
Authors: Coca, A., Li, F., Shiaeles, S., Wu, D. and Liu, F.
Pages: 551-556
Publisher: IEEE
Place of Publication: New York
Abstract:Social networking sites (SNSs) are typically associated with positives such as making friends, they also function on a model that involves a security-threating behaviour called user self-disclosure. Despite numerous efforts to understand the motivation behind self-disclosure on social networking websites, factors influencing this phenomenon are still not fully understood. The data for this study was collected through an online questionnaire that was completed by 95 participants. Results from Spearman’s correlation, One-way ANOVA, and Student’s t-test suggest that privacy concerns, interaction, social trust, trust in the social networking site provider, and gender are significant in predicting self-disclosure on SNSs. The results also show no significant differences in self-disclosure between different age groups, suggesting age as not being a predictor.
https://eprints.bournemouth.ac.uk/40317/
https://www.ieee-csr.org/archive/2024/
Source: BURO EPrints