Rethinking the nature of risk associated with disclosure of personal information
• We are all subject to risks when we reveal our personal data on social media
• These risks are balanced against the benefits of signing up to social media
• This is known as the privacy calculus
• Many attempts have been made to identify those risks and categorise them
• The objective of this research is to gather empirical data to support/challenge the proposed risk model and to produce a robust model that can be used for quantitative studies
It is notoriously difficult to obtain quantitative measures of risk in online environments without access to the large volumes of transactional data generated by use of social media. An alternative approach is to conduct user-focused case studies to identify different types of risk and then use available data to estimate the probability and assess the impact of risk events.
The research builds on my doctoral work focused on the risks associated with access to personal data on online social networking services (SNSs) (Haynes 2015), which tested the idea that personal risk could be used as a way of assessing regulatory effectiveness (Haynes et al. 2016; Haynes & Robinson 2015).
Haynes, D., 2015. Risk and Regulation of Access to Personal Data on Online Social Networking Services in the UK. City University London.
Haynes, D., Bawden, D. & Robinson, L., 2016. A Regulatory Model for Personal Data on Social Networking Services in the UK. International Journal of Information Management, 36(6), pp.872–882.
Haynes, D. & Robinson, L., 2015. Defining User Risk in Social Networking Services. Aslib Journal of Information Management, 67(1), pp.94–115.
This Fellowship is supported by the Royal Academy of Engineering and the Office of the Chief Science Adviser for National Security under the UK Intelligence Community Postdoctoral Fellowship Programme