Human Aspects and Perception of Privacy in Relation to Personalization

TL;DR

This paper explores how human perceptions of privacy influence their interactions with recommender systems, emphasizing the importance of understanding user behaviour to improve privacy and system personalization.

Contribution

It provides insights into user privacy attitudes and proposes methods to better tailor recommender systems by understanding cognitive decision-making processes.

Findings

Factors influencing user privacy disclosure behaviors

Strategies to nudge users towards better privacy decisions

Approaches for privacy adaptation in recommender systems

Abstract

The concept of privacy is inherently intertwined with human attitudes and behaviours, as most computer systems are primarily designed for human use. Especially in the case of Recommender Systems, which feed on information provided by individuals, their efficacy critically depends on whether or not information is externalized, and if it is, how much of this information contributes positively to their performance and accuracy. In this paper, we discuss the impact of several factors on users' information disclosure behaviours and privacy-related attitudes, and how users of recommender systems can be nudged into making better privacy decisions for themselves. Apart from that, we also address the problem of privacy adaptation, i.e. effectively tailoring Recommender Systems by gaining a deeper understanding of people's cognitive decision-making process.