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An Investigation into the Sensitivity of Personal Information and Implications for Disclosure: A UK Perspective

Belen Sağlam, Rahime, Nurse, Jason R. C., Hodges, Duncan (2022) An Investigation into the Sensitivity of Personal Information and Implications for Disclosure: A UK Perspective. Frontiers in Computer Science, . E-ISSN 2624-9898. (doi:10.3389/fcomp.2022.908245) (KAR id:95383)


The perceived sensitivity of information is a crucial factor in both security and privacy concerns and the behaviours of individuals. Furthermore, such perceptions motivate how people disclose and share information with others. We study this topic by using an online questionnaire where a representative sample of 491 British citizens rated the sensitivity of different data items in a variety of scenarios. The sensitivity evaluations revealed in this study are compared to prior results from the US, Brazil and Germany, allowing us to examine the impact of culture. In addition to discovering similarities across cultures, we also identify new factors overlooked in the current research, including concerns about reactions from others, personal safety or mental health and finally, consequences of disclosure on others. We also highlight a difference between the regulatory perspective and the citizen perspective on information sensitivity.

We then operationalised this understanding within several example use-cases exploring disclosures in the healthcare and finance industry, two areas where security is paramount. We explored the disclosures being made through two different interaction means: directly to a human or chatbot mediated (given that an increasing amount of personal data is shared with these agents in industry). We also explored the effect of anonymity in these contexts. Participants showed a significant reluctance to disclose information they considered `irrelevant' or `out of context' information disregarding other factors such as interaction means or anonymity. We also observed that chatbots proved detrimental to eliciting sensitive disclosures in the healthcare domain; however, within the finance domain, there was less effect. This article's findings provide new insights for those developing online systems intended to elicit sensitive personal information from users.

Item Type: Article
DOI/Identification number: 10.3389/fcomp.2022.908245
Uncontrolled keywords: Personal information disclosure, information sensitivity, Privacy, Chatbots, Personal Information
Subjects: B Philosophy. Psychology. Religion > BF Psychology
H Social Sciences
Q Science > QA Mathematics (inc Computing science)
T Technology
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
University-wide institutes > Institute of Cyber Security for Society
Depositing User: Jason Nurse
Date Deposited: 10 Jun 2022 20:40 UTC
Last Modified: 19 Nov 2022 17:43 UTC
Resource URI: (The current URI for this page, for reference purposes)

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