Understanding the impact of group characteristics on individual’s privacy behavior–a systematic literature review

As a result of on-going digital transformation, privacy concerns and resulting privacy behavior play an important role in everyone’s life and affect both individuals as well as groups of individuals. However, there is a lack of literature on the impact of group characteristics on individual privacy behavior. Thus, the goal of this work is to provide an overview of the group-level factors that influence an individuals’ privacy behavior. By conducting a systematic literature review, we identified a total of 14 articles which investigate several factors influencing privacy behavior on the group-level. We find the theory of multilevel information privacy (TMIP) as most promising avenue to understand the role of group factors for individual privacy behavior and extend TMIP by group characteristics, group behaviors, as well as privacy concerns. Finally, even though several papers investigated the impact of group factors, there is still a big need for more research in this area

Taiwanese university students’ smartphone use and the privacy paradox

With the prevalence of smart devices and wireless Internet, privacy has become a pivotal matter in governmental, academic, and technological fields. Our study aims to understand Taiwanese university students’ privacy concerns and protective behaviours in relation to online targeting ads and their habitual smartphone usage. Surveying 810 valid subjects, our results first propose that ad relevance has direct bearing on attention to ads. Second, ad relevance inversely correlates with privacy concerns (i.e. descending personal control and surging corporate power) and protective behaviours (self-filtering and ad evasion). Third and finally, neither privacy concerns nor protective behaviours have a negative bearing on habitual smartphone usage. Opposite to previous research, our study concludes that Taiwanese college students exhibit zero privacy paradox, owing to no signs of privacy concern incited by mobile targeting ads, no evidence of significant protective behaviours, and no decreasing habitual smartphone usage out of privacy concern and protection. Our findings indicate Taiwanese university students’ shaky awareness of potential risks and crises from exposure to vulnerable online privacy management. To deal with this, we suggest educating youths’ understandings of digital jeopardy by experts is urgently needed more so than just technical tutorials of privacy settings

Digital Rights and Responsibility in Education: A Scoping Review

Studies on digital rights in education have both gained attention and provided a framework for research, policy and practice in educational research within the field of educational technology. The potential benefits we appreciate in Internet use are inseparable from the maximum risks involved. Faced with this responsibility, individuals demand that their rights and freedoms be guaranteed in the digital environment according to their various roles as students, teachers, families or staff. This scoping review selects and analyses 54 theoretical and empirical studies from the last decade (2013-2023), identifying the main topics investigated as privacy protection in online environments, right to digital security or cybersecurity, and right to digital education. The review underscores the need to guide efforts towards digital education for citizens because the legal regulation of rights and responsibilities is necessary but insufficient. The paper also makes arguments about acceptance, limitations and implications for teacher training.European Regional Development Fund’s 2014-2020 Operational Program, the Andalusian Government, and Spain’s Department of Economic Transformation, Industry, Knowledge and Universities (Project A.SEJ.46.UGR 2020)

Exacerbating Mindless Compliance: The Danger of Justifications during Privacy Decision Making in the Context of Facebook Applications

Online companies exploit mindless compliance during users’ privacy decision making to avoid liability while not impairing users’ willingness to use their services. These manipulations can play against users since they subversively influence their decisions by nudging them to mindlessly comply with disclosure requests rather than enabling them to make deliberate choices. In this paper, we demonstrate the compliance-inducing effects of defaults and framing in the context of a Facebook application that nudges people to be automatically publicly tagged in their friends’ photos and/or to tag their friends in their own photos. By studying these effects in a Facebook application, we overcome a common criticism of privacy research, which often relies on hypothetical scenarios. Our results concur with previous findings on framing and default effects. Specifically, we found a reduction in privacy-preserving behaviors (i.e., a higher tagging rate in our case) in positively framed and accept-by-default decision scenarios. Moreover, we tested the effect that two types of justifications—information that implies what other people do (normative) or what the user ought to do (rationale based)— have on framing- and default-induced compliance. Existing work suggests that justifications may increase compliance in a positive (agree-by-) default scenario even when the justification does not relate to the decision. In this study, we expand this finding and show that even a justification that is opposite to the default action (e.g., a justification suggesting that one should not use the application) can increase mindless compliance with the default. Thus, when companies abide by policy makers’ requirements to obtain informed user consent through explaining the privacy settings, they will paradoxically induce mindless compliance and further threaten user privacy

Familiarity with Big Data, Privacy Concerns, and Self-disclosure Accuracy in Social Networking Websites: An APCO Model

Social networking websites have not only become the most prevalent communication tools in today’s digital age but also one of the top big data sources. Big data advocates promote the promising benefits of big data applications to both users and practitioners. However, public polls show evidence of heightened privacy concerns among Internet and social media users. We review the privacy literature based on protection motivation theory and the theory of planned behavior to develop an APCO model that incorporates novel factors that reflect users’ familiarity with big data. Our results, which we obtained from using a cross-sectional survey design and structural equation modeling (SEM) techniques, support most of our proposed hypotheses. Specifically, we found that that awareness of big data had a negative impact on and awareness of big data implications had a positive impact on privacy concerns. In turn, privacy concerns impacted self-disclosure concerns positively and self-disclosure accuracy negatively. We also considered other antecedents of privacy concerns and tested other alternative models to examine the mediating role of privacy concerns, to control for demographic variables, and to investigate different roles of the trust construct. Finally, we discuss the results of our findings and the theoretical and practical implications

Framing and Measuring Multi-dimensional Interpersonal Privacy Preferences of Social Networking Site Users

In this paper, we focus on interpersonal boundary regulation as a means to balance the tradeoffs between engaging with others and protecting one’s privacy on social networking sites (SNSs). We examine boundary regulation from the combined perspectives of SNS design and end user behavior; we conduct a feature-oriented domain analysis of five popular SNS interfaces and 21 semi-structured SNS user interviews. We use this information to construct a taxonomy of 10 types of interpersonal boundaries SNS users regulate to manage their privacy preferences. We then develop and validate scales to operationalize these 10 boundary types to measure the multi-dimensional nature of SNS users’ privacy preferences by using a sample of 581 Facebook users. Our taxonomy provides a theoretical foundation for conceptualizing SNS user privacy, and our scales provide a more robust way to measure SNS users’ multi-faceted privacy preferences