Privacy Salience: Taxonomies and Research Opportunities

TL;DR

This paper develops comprehensive taxonomies of privacy salience by analyzing existing studies, highlighting research gaps, and proposing new directions to better understand privacy perceptions in digital environments.

Contribution

It introduces the first taxonomies of privacy salience, categorizes prior research, and identifies overlooked opportunities such as targeted advertising and IoT privacy studies.

Findings

Web browsing is frequently analyzed in privacy salience studies.

Internet-of-Things privacy research is limited.

Potential research opportunities include targeted advertising and social network salience.

Abstract

Privacy is a well-understood concept in the physical world, with us all desiring some escape from the public gaze. However, while individuals might recognise locking doors as protecting privacy, they have difficulty practising equivalent actions online. Privacy salience considers the tangibility of this important principle; one which is often obscured in digital environments. Through extensively surveying a range of studies, we construct the first taxonomies of privacy salience. After coding articles and identifying commonalities, we categorise works by their methodologies, platforms and underlying themes. While web browsing appears to be frequently analysed, the Internet-of-Things has received little attention. Through our use of category tuples and frequency matrices, we then explore those research opportunities which might have been overlooked. These include studies of targeted advertising and its affect on salience in social networks. It is through refining our understanding of this important topic that we can better highlight the subject of privacy.