Misinformation interventions are often evaluated under ideal conditions, yet real-world systems are rarely flawless. We report on an online experiment (N = 1, 004) comparing five state-of-the-art interventions – inoculation, accuracy prompt, community note, fact-check, and indicators – across TikTok, Telegram, and X. We examined efficacy and user perceptions under flawless and erroneous implementations. Misinformation accompanied by fact-checks and indicators was rated as significantly less accurate, while community notes showed weaker effects. Modality did not significantly influence intervention efficacy and had only minor effects on user acceptance. Community notes, fact-checks, and indicators were rated as more helpful but also more annoying than the less informative accuracy prompts. Notably, the efficacy of interventions disappeared under erroneous conditions. This highlights the crucial role of intervention quality in fostering trust and acceptance. Our findings provide (1) a cross-platform evaluation of interventions and (2) empirical evidence that accuracy and reliability are crucial in complex social media environments.

The ongoing challenge of misinformation on social media motivates ongoing efforts to find effective countermeasures. In this study, we evaluated the potential of personalised nudging to reduce the sharing of misinformation on social media, as personalised support has been successfully applied in other areas of critical information handling. In an online experiment (N = 396) exposing users to social media posts, we assessed the degree of misinformation sharing between groups receiving (1) no nudges, (2) non-personalised nudges, and (3) personalised nudges. Personalisation was based on three psychometric dimensions - general decision-making style, consideration of future consequences, need for cognition - to assign the most appropriate nudge from a pool of five nudges. The results showed significant differences (p < .05) between all three groups, with the personalised nudge group sharing the least misinformation. Detailed analyses at the nudge level revealed that one nudge was universally effective and two nudges were effective only in their personalised form. The results generally confirm the potential of personalisation, although the effect is limited in scope. These findings shed light on the nuanced results of nudging studies, highlight the benefits of personalisation, and raise ethical considerations regarding the privacy implications of personalisation and those inherent in nudges.

Misinformation poses a recurrent challenge for video-sharing platforms (VSPs) like TikTok. Obtaining user perspectives on digital interventions addressing the need for transparency (e.g., through indicators) is essential. This article offers a thorough examination of the comprehensibility, usefulness, and limitations of an indicator-based intervention from an adolescents’ perspective. This study (N = 39; aged 13-16 years) comprised two qualitative steps: (1) focus group discussions and (2) think-aloud sessions, where participants engaged with a smartphone-app for TikTok. The results offer new insights into how video-based indicators can assist adolescents’ assessments. The intervention received positive feedback, especially for its transparency, and could be applicable to new content. This paper sheds light on how adolescents are expected to be experts while also being prone to video-based misinformation, with limited understanding of an intervention’s limitations. By adopting teenagers’ perspectives, we contribute to HCI research and provide new insights into the chances and limitations of interventions for VSPs.

Browser cookies, especially those from third parties, pose a threat to individual privacy. While it is possible in principle to control the number of cookies accepted, this choice is often neither usable nor truly informed. To address this issue, this study used semi-structured interviews (N=19) to identify attitudes and user requirements to develop an alternative personalised cookie banner, which was evaluated in an online experiment (N=157). The cookie banner explanations were tailored to the privacy knowledge of three groups of users: low, medium and high. The online experiment measured cookie choices and perceived usability of the cookie banner across three groups: an experimental group that viewed the novel cookie banner with personalisation (personalised privacy assistant), a control group that viewed the novel cookie banner without personalisation (privacy assistant) and a control group that viewed the standard cookie banner provided by the website. The results indicate that the novel cookie banner (with or without personalisation) generally resulted in significantly fewer accepted cookies and increased usability compared to the standard cookie window. In addition, the personalised cookie banner resulted in significantly fewer accepted cookies and higher usability than the non-personalised cookie banner. These results suggest that tailoring cookie banners to users' privacy knowledge can be an effective approach to empowering users to make informed choices and better protect their privacy.

In many applications and websites people use in their everyday life, their privacy and data are threatened, e.g., by script tracking during browsing. Although researchers and companies have developed privacy-enhancing technologies (PETs), they are often difficult to use for lay users. In this paper, we conducted a literature review to classify users into different extit{support personas} based on their privacy competence and privacy concern. With developers of PETs in mind, support personas were envisioned to facilitate the customization of software according to the support needs of different users. In order to demonstrate the usefulness of support personas and based on workshop sessions with 15 participants, we designed a browser extension that supports users with the issue of script tracking by providing different user interfaces for different support personas. The following qualitative evaluation with 31 participants showed that the developed UI elements worked as intended for the different support personas. Therefore, we conclude the concept of support personas is useful in the development process of usable applications that enhance the privacy of the users while also educating them and thus potentially increasing their privacy literacy.

The use of Open Source Intelligence (OSINT) to monitor and detect cybersecurity threats is gaining popularity among Cybersecurity Emergency or Incident Response Teams (CERTs/CSIRTs). They increasingly use semi-automated OSINT approaches when monitoring cyber threats for public infrastructure services and incident response. Most of the systems use publicly available data, often focusing on social media due to timely data for situational assessment. As indirect and affected stakeholders, the acceptance of OSINT systems by users, as well as the conditions which influence the acceptance, are relevant for the development of OSINT systems for cybersecurity. Therefore, as part of the ethical and social technology assessment, we conducted a survey (N=1,093), in which we asked participants about their acceptance of OSINT systems, their perceived need for open source surveillance, as well as their privacy behavior and concerns. Further, we tested if the awareness of OSINT is an interactive factor that affects other factors. Our results indicate that cyber threat perception and the perceived need for OSINT are positively related to acceptance, while privacy concerns are negatively related. The awareness of OSINT, however, has only shown effects on people with higher privacy concerns. Here, particularly high OSINT awareness and limited privacy concerns were associated with higher OSINT acceptance. Lastly, we provide implications for further research and the use of OSINT systems for cybersecurity by authorities. As OSINT is a framework rather than a single technology, approaches can be selected and combined to adhere to data minimization and anonymization as well as to leverage improvements in privacy-preserving computation and machine learning innovations. Regarding the use of OSINT, the results suggest to favor approaches that provide transparency to users regarding the use of the systems and the data they gather.

Concise instruments to determine privacy personas – typical privacy-related user groups – are not available at present. Consequently, we aimed to identify them on a privacy knowledge–privacy behavior ratio based on a self-developed instrument. To achieve this, we conducted an item analysis (N = 820) and a confirmatory factor analysis (CFA) (N = 656) of data based on an online study with German participants. Starting with 81 items, we reduced those to an eleven-item questionnaire with the two scales privacy knowledge and privacy behavior. A subsequent cluster analysis (N = 656) revealed three distinct user groups: (1) Fundamentalists scoring high in privacy knowledge and behavior, (2) Pragmatists scoring average in privacy knowledge and behavior and (3) Unconcerned scoring low in privacy knowledge and behavior. In a closer inspection of the questionnaire, the CFAs supported the model with a close global fit based on RMSEA in a training and to a lesser extent in a cross-validation sample. Deficient local fit as well as validity and reliability coefficients well below generally accepted thresholds, however, revealed that the questionnaire in its current form cannot be considered a suitable measurement instrument for determining privacy personas. The results are discussed in terms of related persona conceptualizations, the importance of a methodologically sound investigation of corresponding privacy dimensions and our lessons learned.