The effect of privacy concerns, interaction, trust, age, and gender on self-disclosure behaviours on social networking sites

Alexis Coca, Fudong Li, Stavros Shiaeles, Deha Wu, Fan Liu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.
Original languageEnglish
Title of host publication2024 IEEE International Conference on Cyber Security and Resilience (CSR)
PublisherIEEE/ IAPR
Pages551-556
Number of pages6
ISBN (Electronic)9798350375367
ISBN (Print)9798350375374
DOIs
Publication statusPublished - 4 Sept 2024
Event2024 IEEE International Conference on Cyber Security and Resilience (CSR) - London, United Kingdom
Duration: 2 Sept 20244 Sept 2024

Conference

Conference2024 IEEE International Conference on Cyber Security and Resilience (CSR)
Period2/09/244/09/24

Keywords

  • Knowledge engineering
  • Privacy
  • Correlation
  • Social networking (online)
  • Computer crime
  • Analysis of variance
  • Resilience

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