"It wouldn't happen to me": Privacy concerns and perspectives following the Cambridge Analytica scandal. Issue 143 (November 2020)

• Record Type: Journal Article
• Authors: Hinds, Joanne; Williams, Emma J.; Joinson, Adam N.
• Is Part Of: International journal of human-computer studies. Issue 143(2020)
• Publication Date: 2020-11
• Subjects: Facebook -- Cybersecurity -- Targeted advertising -- Data breach -- Privacy fatigue -- Networked privacy; Human-machine systems -- Periodicals; Systems engineering -- Periodicals; Human engineering -- Periodicals; Human engineering; Human-machine systems; Systems engineering; Periodicals; Electronic journals; 004.019
• DOI: 10.1016/j.ijhcs.2020.102498
• Languages: English
• ISSNs: 1071-5819

Abstract

Highlights: People did not delete their Facebook accounts due to the Cambridge Analytica scandal. Online privacy is confusing and people lack knowledge of risks relating to their networks. People feel reluctant to update their settings due to 'endless' data breaches and updates. Abstract: In March 2018, news of the Facebook-Cambridge Analytica scandal made headlines around the world. By inappropriately collecting data from approximately 87 million users' Facebook profiles, the data analytics company, Cambridge Analytica, created psychographically tailored advertisements that allegedly aimed to influence people's voting preferences in the 2016 US presidential election. In the aftermath of this incident, we conducted a series of semi-structured interviews with 30 participants based at a UK university, discussing their understanding of online privacy and how they manage it in the wake of the scandal. We analysed this data using an inductive (i.e. 'bottom-up') thematic analysis approach. Contrary to many opinions reported in the news, the respondents in our sample did not delete their accounts, frantically change their privacy settings, or even express that much concern. As a result, individuals often consider themselves immune to psychographically tailored advertisements, and lack understanding of how automated approaches and algorithms work in relation to their (and their networks') personal data. We discuss our findings in relation to wider related research (e.g. crisis fatigue, networked privacy, Protection Motivation Theory) and discuss directions for future research.