Enhancing the privacy risk awareness of teenagers in online social networks through soft-paternalism mechanisms

Abstract

Privacy Risk in Online Social Networks (OSNs) is one of the main concerns that has increased in the last few years. Even though social network applications provide mechanisms to control risk, teenagers are not often aware of the privacy risks of disclosing information in online social networks. The privacy decision-making process is complex and users often do not have full knowledge and enough time to evaluate all potential scenarios. They do not consider the audience that will have access to disclosed information or the risk if the information continues to spread and reaches an unexpected audience. To deal with these issues, we propose two soft-paternalism mechanisms that provide information to the user about the privacy risk of publishing information on a social network. That privacy risk is based on a complex privacy metric. To evaluate the mechanisms, we performed an experiment with 42 teenagers. The proposed mechanisms were included in a social network called Pesedia. The results show that there are significant differences in teenagers' behaviors towards better privacy practices when the mechanisms are included in the network.

Measures of Privacy Protection on Social Environments

“…Finally, the participants considered for the experiments have a certain age distribution (approx. [12][13][14]. Therefore, these results cannot be extrapolated to users that are in other age range.…”

“…Schöning et al [222] tested significant differences by personalizing the styles of the nudges shown. Alemany et al [12] tested personalized nudges based on an estimation of the final audience before posting. In that work, the authors reported that teenagers used more restrictive policies when they were aware of the potential audience.…”

“…Chapter 7 (previously published in [12]) presents different kinds of privacy mechanisms based on soft-paternalistic mechanisms (i.e., nudges) that inform users about the potential consequences of their privacy decisions. In this work, the privacy mechanisms are developed and integrated into the social network PESEDIA and are finally tested in a study with real users.…”

“…All of these works converge to a clear premise: not all of the personal information has the same value. Legislation such as the GDPR 11 , NIST 12 , or UKAN 13 (which emerged from the need to protect users' data) distinguishes different levels of data sensitivity. Companies that buy, sell, and exchange users' data as an economic resource also consider different values for data based on the kind of information provided and whether they can link it to other data [172].…”

“…PESEDIA was designed as a tool for the teaching/learning of OSN features and to increase concern, awareness, and seeking behavior on privacy, especially in the case of children and teenagers who are just beginning to use OSNs. The main goals of PESEDIA include: (i) the design and development of new metrics to analyze and quantify privacy risks [11,13]; (ii) the application of methods to influence users' behavior towards safer actions regarding their privacy [12]; and (iii) the evaluation and testing of new proposals with real users [14]. The underlying implementation of PESEDIA uses Elgg [64], which is an open-source engine that is used to build social environments.…”