Privacy calculus on social networks?

Social networks on mobile applications are used more and more by everyone. Businesses and individuals use platforms like Twitter, Facebook, Instagram, WhatsApp, YouTube, and many others as sources of entertainment and income. However, the increase in use and public engagement on those platforms has also caused a significant increase in user privacy risks. Computers and mobile phones contain sensors to collect data. The information collected can be about users’ social lives by identifying their location and all kinds of geographical data such as places frequented. Manufacturers and application developers mainly use this information to improve the customer experience and provide targeted advertising. According to Vallina-Rodriguez and Syndaresan (2017), more than 70% of mobile apps report their user’s data to a third party in exchange for money.

This impressive growth of applications using their users’ information is worrying in terms of privacy. In the literature on information privacy, the privacy calculus theory is often applied. This theory examines the cost and benefit of disclosing information. The costs generally result in the loss of the user’s privacy, while the benefits are the gains obtained in exchange for personals information, such as access to a social network platform.

This study aims to assess the costs and benefits of engaging with mobile social networks based on studies using privacy calculus theory. Specifically, the researchers will use the framework for calculating confidentiality by separating the effects of institutional and social confidentiality on engagement. Therefore, they do not examine it as a whole; the aim is to observe the differences between these two types of confidentiality issues. To do this, the researchers distributed a questionnaire to 354 users of the peer-to-peer (P2P) social payment application selected through Amazon’s Mechanical Turk platform.

Here are the main results of the study:

1. The risk of confidentiality is positively related to social confidentiality issues.

2. Privacy control is negatively associated with social privacy concerns.

3. Information sensitivity is positively linked to institutional concerns about confidentiality.

4. Institutional privacy concerns are negatively correlated to engagement.

5. Social privacy concerns are negatively related to engagement.

Briefly, the results show that institutional and social concerns decrease engagement. At the antecedent level, the perceived sensitivity of information leads to increased institutional confidentiality issues. However, social privacy issues are influenced by the perception of risk and control. Precisely, the more individuals who believe they have control and understand the risks involved on a platform, the more they tend to pay more attention and use the application less in the long term.

In addition to its considerable empirical contribution, the study emphasizes that policymakers should seek to raise awareness among users on aspects of perceived privacy on applications that sell information for companies’ benefit. Furthermore, application developers should be transparent and provide their users with the ability to protect their data. Future research could broaden the study’s representativeness by comparing the results with a different age population, for example, baby boomers and the new teenager’s generation.

To cite: Jozani, M., Ayaburi, E., Ko, M., Raymond-Choo, K. (2020). Privacy concerns and benefits of engagement with social media-enabled apps: A privacy calculus perspective. Computers in Human Behavior, 107.