User Modeling for Privacy-preserving Explanations in Group Recommendations

My thesis investigates what makes good explanations for group recommendations, considering the privacy concerns of group members. Let’s give an example. Have you ever been to lunch with other colleagues on a business trip? Do you recall how long it took you to pick a restaurant? In these situations, recommender systems could help people decide,...

Rethinking consumers' data sharing decisions with the emergence of multi-party computation: An experimental design for evaluation

Consumers are increasingly reluctant to share their personal data with businesses due to mounting concerns over privacy and control. Emerging privacy-enhancing technologies like multi-party computation (MPC), which allows generating insights while consumers retain data control, are challenging the current understanding of why consumers share...

Factors influencing privacy concern for explanations of group recommendation

Explanations can help users to better understand why items have been recommended. Additionally, explanations for group recommender systems need to consider further goals than single-user recommender systems. For example, we need to balance group members' need for privacy with their need for transparency, since a transparent explanation might...

Exploring User Concerns about Disclosing Location and Emotion Information in Group Recommendations

Recent research has shown that explanations serve as an important means to increase transparency in group recommendations while also increasing users' privacy concerns. However, it is currently unclear what personal and contextual factors affect users' privacy concerns about various types of personal information. This paper studies the effect...

Engagement in proactive recommendations: The role of recommendation accuracy, information privacy concerns and personality traits

The present research explored to what extent user engagement in proactive recommendation scenarios is influenced by the accuracy of recommendations, concerns with information privacy, and trait personality. We hypothesized that people’s self-reported information privacy concerns would matter more when they received accurate (vs. inaccurate)...

An exploratory study in the concerns for information privacy: Finding a trend, factors of influence and spheres of informational justice

In this research a quantitative metaanalysis was conducted on the Concern For Information Privacy construct (CFIP) and its dimensions to find a trend. This study concluded that on a global scale, people’s concerns for unauthorized secondary use and improper access of their personal information have increased, and that for a general/student...

Acceptance of Privacy-Sensitive Technologies: Smart Metering Case in The Netherlands

Over recent years there have been several initiatives around the world that aim to roll out smart metering systems, especially within North America and member states of the European Union. Smart metering systems, giving essential conditions for smart grids in the energy sector, can offer services aimed at achieving many different goals beyond...