User surveys are essential to user-centered research in many fields, including human-computer interaction (HCI). Survey personalization—specifically, adapting questionnaires to the respondents’ profiles and experiences—can improve reliability and quality of responses. However, popular survey platforms lack usable mechanisms for seamlessly importing participants’ data from other systems. This paper explores the design of a data-driven survey system to fill this gap. First, we conducted formative research, including a literature review and a survey of researchers (N = 52), to understand researchers’ practices, experiences, needs, and interests in a data-driven survey system. Then, we designed and implemented a minimum viable product called Data-Driven Surveys (DDS), which enables including respondents’ data from online service accounts (Fitbit, Instagram, and GitHub) in survey questions, answers, and flow/logic on existing survey platforms (Qualtrics and SurveyMonkey). Our system is open source and can be extended to work with more online service accounts and survey platforms. It can enhance the survey research experience for both researchers and respondents. A demonstration video is available here: https://doi.org/10.17605/osf.io/vedbj

Second-hand electronic devices are increasingly being sold online. Although more affordable and more environment-friendly than new products, second-hand devices, in particular those with storage capabilities, create security and privacy threats (e.g., malware or confidential data still stored on the device, aka remnant data). Previous work studied this issue from a technical point of view or only from the perspective of the sellers of the devices, but the perspective of the buyers has been largely overlooked. In this paper, we fill this gap and take a multi-disciplinary approach, focusing on the case of Switzerland. First, we conduct a brief legal analysis of the rights and obligations related to second-hand storage devices. Second, in order to understand the buyers' practices related to these devices and their beliefs about their legal rights and obligations, we deploy a survey in collaboration with a major online platform for transactions of second-hand goods. We demonstrate that the risks highlighted in prior research might not materialize, as many buyers do not inspect the content of the bought devices (e.g., they format it directly). We also found that none of the buyers uses forensic techniques. We identified that the buyers' decisions about remnant data depend on the type of data. For instance, for data with illegal content, they would keep the data to report it to the authorities, whereas for sensitive personal data they would either delete the data or contact the sellers. We identified several discrepancies between the actual legal rights/obligations and users' beliefs.

Wearable activity trackers (WATs) have recently gained worldwide popularity, with over a billion devices collecting a range of personal data. To receive additional services, users commonly share this data with third-party applications (TPAs). However, this practice poses potential privacy risks. Privacy-enhancing technologies have been developed to address these concerns, but they often lack user-centered design, and therefore, are less likely to be directly related to users' concerns and to be widely adopted. This study takes a participatory design approach involving N=26 experienced WAT users who share data with TPAs. Through a series of design sessions, participants conceptualized 19 solutions, from which we identified seven different design features. We further analyze and discuss how these features can be combined to assist users in managing their data sharing with TPAs and, therefore, enhancing their privacy. Finally, we selected the three most promising features, namely partial sharing, reminder, and revocation assistance, and conducted an online survey with N=201 WAT users to better understand the potential effectiveness and usability of these features. This work makes an important contribution by offering user-centered solutions and valuable insights for integrating privacy-enhancing technologies into the WAT ecosystem.

Internet users possess accounts on dozens of online services where they are often identified by one of their e-mail addresses. They often use the same address on multiple services and for communicating with their contacts. In this paper, we investigate attacks that enable an adversary (e.g., company, friend) to determine (stealthily or not) whether an individual, identified by their e-mail address, has an account on certain services (i.e., an account enumeration attack ). Such attacks on account privacy have serious implications as information about one’s accounts can be used to (1) profile them and (2) improve the effectiveness of phishing. We take a multifaceted approach and study these attacks through a combination of experiments (63 services), surveys (318 respondents), and focus groups (13 participants). We demonstrate the high vulnerability of popular services (93.7%) and the concerns of users about their account privacy, as well as their increased susceptibility to phishing e-mails that impersonate services on which they have an account. We also provide findings on the challenges in implementing countermeasures for service providers and on users’ ideas for enhancing their account privacy. Finally, our interaction with national data protection authorities led to the inclusion of recommendations in their developers’ guide.

In recent years, various initiatives from within and outside the HCI field have encouraged researchers to improve research ethics, openness, and transparency in their empirical research. We quantify how the CHI literature might have changed in these three aspects by analyzing samples of 118 CHI 2017 and 127 CHI 2022 papers—randomly drawn and stratified across conference sessions. We operationalized research ethics, openness, and transparency into 45 criteria and manually annotated the sampled papers. The results show that the CHI 2022 sample was better in 18 criteria, but in the rest of the criteria, it has no improvement. The most noticeable improvements were related to research transparency (10 out of 17 criteria). We also explored the possibility of assisting the verification process by developing a proof-of-concept screening system. We tested this tool with eight criteria. Six of them achieved high accuracy and F1 score. We discuss the implications for future research practices and education.

Sharing multimedia content, without obtaining consent from the people involved causes multiparty privacy conflicts (MPCs). However, social-media platforms do not proactively protect users from the occurrence of MPCs. Hence, users resort to out-of-band, informal communication channels, attempting to mitigate such conflicts. So far, previous works have focused on hard interventions that do not adequately consider the contextual factors (e.g., social norms, cognitive priming) or are employed too late (i.e., the content has already been seen). In this work, we investigate the potential of conversational agents as a medium for negotiating and mitigating MPCs. We designed MediationBot, a mediator chatbot that encourages consent collection, enables users to explain their points of view, and proposes solutions to finding a middle ground. We evaluated our design using a Wizard-of-Oz experiment with N = 32 participants, where we found that MediationBot can effectively help participants to reach an agreement and to prevent MPCs. It produced a structured conversation where participants had well-clarified speaking turns. Overall, our participants found MediationBot to be supportive as it proposes useful middle-ground solutions. Our work informs the future design of mediator agents to support social-media users against MPCs.

Disclosing personal information significantly increases the likelihood of incidents of cyberbullying. This highlights the significance of investigating the relationships between various stakeholders in cyberbullying incidents. Our objective is to gain insight into the roles of the stakeholders, types, and typical paths of personal information in cyberbullying incidents. To achieve this, we conducted a large-scale survey with a representative sample of internet users from the United States and Nigeria (N = 1555). Our findings indicate that cyberbullying is often fueled by personal information that becomes known, directly or through social media, to other stakeholders. Cyberbullying incidents involve more than just attackers and victims; they can involve other stakeholders as third-parties 'disclosers' Both strangers and friends typically engage in such activities. Cyberbullying incidents are twice as common in Nigeria as in the United States. Our findings have implications for design, social-media literacy programs, and policy.

The number of users of wearable activity trackers (WATs) has rapidly increased over the last decade. Although these devices enable their users to monitor their activities and health, they also raise new security and privacy concerns, given the sensitive data (e.g., steps, heart rate) they collect and the information that can be inferred from this data (e.g., diseases). In addition to sharing with the service providers (e.g., Fitbit), WAT users can share their fitness data with third-party applications (TPAs) and individuals. Understanding how and with whom users share their fitness data and what kind of approaches they take to preserve their privacy are key to assessing the underlying privacy risks and to further designing appropriate privacy-enhancing techniques. In this work, we perform, through a large-scale survey of N=628 WAT users, the first quantitative and qualitative analysis of users' awareness, understanding, attitudes, and behaviors toward fitness-data sharing with TPAs and individuals. By asking these users to draw their thoughts, we explore, in particular, users' practices and actual behaviors toward fitness-data sharing and their mental models. Our empirical results show that about half of WAT users underestimate the number of TPAs to which they have granted access to their data, and 63% share data with at least one TPA that they do not actively use (anymore). Furthermore, 29% of the users do not revoke TPA access to their data because they forget they gave access to it in the first place, and 8% were not even aware they could revoke access to their data. Finally, their mental models, as well as some of their answers, demonstrate substantial gaps in their understanding of the data-sharing process. Importantly, 67% of the respondents think that TPAs cannot access the fitness data that was collected before they granted access to it, whereas TPAs actually can do this.

Abstract The paper presents a qualitative study to explore the use of fitness trackers and their social functions in intergenerational settings. The study covered three phases of semi-structured interviews with older and younger adults during individual and intergenerational use of the fitness trackers. The study revealed comparability as common fitness practice for older adults. The findings show that intergenerational fitness tracking practices can increase in-person meetings and daily discourses and thus enhance family social bonds. An unexpected benefit of this practice is its ability to help older adults overcome technology barriers related to the use of fitness trackers. Overall speaking, families whose intergenerational members already enjoy a strong relationship are likely to gain the most from such practices. Many challenges remain especially concerning the motivation and involvement of younger partners and the user experience design aspect of such digital programs. For this purpose, we have developed some recommendations for the future development and deployment of intergenerational fitness tracking systems to stimulate interactions between younger and older family members and thus to promote their physical and emotional well-being.

Although sharing multimedia content on online social networks (OSNs) has many benefits, publishing photos or videos of other people—without obtaining permission—can cause multiparty privacy conflicts (MPCs). Early studies developed technical solutions and dissuasive approaches to address MPCs. However, none of these studies involved, in the design process, the OSN users who have experienced MPCs. Hence, they possibly overlooked the valuable experiences these individuals have accrued. To fill this gap, we recruited participants specifically from this population of users, and we involved them in participatory design sessions to find solutions to reduce the incidence of MPCs. To frame the activities of our participants, we borrowed terminology and concepts from a well-known framework used in the justice systems. Over the course of several design sessions, our participants designed 10 solutions to mitigate MPCs. The designed solutions are based on different mechanisms, including preventing MPCs from occurring, dissuading users from sharing, resolving the conflicts, and educating users about community standards. We discuss the open design and research opportunities suggested by the designed solutions and contribute an ideal workflow that synthesizes the best of each solution. We contribute to the innovation of privacy-enhancing technologies to limit the incidence of MPCs in OSNs.

Individuals share increasing amounts of personal multimedia data, exposing themselves (uploaders) as well as others (data subjects). Non-consensual sharing of multimedia data that depicts others raises so-called multiparty privacy conflicts (MPCs), which can have severe consequences. To limit the incidence of MPCs, a family of Precautionary mechanisms have recently been developed that force uploaders to collaborate with the other data subjects to prevent MPCs. However, there is still very little work on understanding how users perceive the precautionary mechanisms together with which ones they prefer and why. In addition, precautionary mechanisms have some limitations, e.g., they require linking content to the co-owners' identity. Therefore, we also explore alternatives to precautionary mechanisms and propose a new class of solutions-Dissuasive mechanisms-that aim at deterring the uploaders from sharing without consent. We then present a user-centric comparison of precautionary and dissuasive mechanisms, through a large-scale survey (N = 1792; a representative sample of adult Internet users). Our results showed that respondents prefer precautionary to dissuasive mechanisms. These enforce collaboration, provide more control to the data subjects, but also they reduce uploaders' uncertainty around what is considered appropriate for sharing. We learned that threatening legal consequences is the most desirable dissuasive mechanism, and that respondents prefer the mechanisms that threaten users with immediate consequences (compared with delayed consequences). Dissuasive mechanisms are in fact well received by frequent sharers and older users, while precautionary mechanisms are preferred by women and younger users. We discuss the implications for design, including considerations about side leakages, consent collection, and censorship.

Mindfulness practices are well-known for their benefits to mental and physical well-being. Given the prevalence of smartphones, mindfulness applications have attracted growing global interest. However, the majority of existing applications use guided meditation that is not adaptable to each user's unique needs or pace. This article proposes a novel framework called Attention Regulation Framework (ARF) , which studies how more flexible and adaptable mindfulness applications could be designed, beyond guided meditation and toward self-regulated meditation. ARF proposes mindfulness interaction design guidelines and interfaces whereby practitioners naturally and constantly bring their attention back to the present moment and develop non-judgmental awareness. This is achieved by the performance of subtle movements, which are supported by non-intrusive detection-feedback mechanisms. We used two design cases to demonstrate ARF in static and kinetic meditation conditions. We conducted four user evaluation studies in unique situations where ARF is particularly effective, vis-à-vis mindfulness practice in busy environments and mindfulness interfaces that adapt to the pace of the user. The studies show that the design cases, compared with guided meditation applications, are more effective in improving attention, mindfulness, mood, well-being, and physical balance. Our work contributes to the development of self-regulated mindfulness technologies.

In our fast-paced society, stress and anxiety have become increasingly common. Meditation for relaxation has received much attention. Meditation apps exploit various senses, e.g., touch, audio and vision, but the relationship between human senses and interactive meditation is not well understood. This paper empirically evaluates the effects of single and combined human senses on interactive meditation. We found that the effectiveness of human senses can be defined by their respective roles in maintaining the balance between relaxation and focus. This work is the first to attempt to understand these relationships. The findings have broad implications for the field of multi-modal interaction and interactive meditation applications.

We are often overwhelmed by everyday stressors. Mindfulness meditation can help slow things down and bring one's attention into the present moment. Given the prevalence of smartphones, mindfulness-based mobile applications (MBMAs) have received much attention. Current MBMAs mainly use the guided meditation method which may not be always effective, e.g., users may not be able to follow the pace of instructions and they need a private environment. This paper presents a framework for interactive MBMAs which allows users to self-regulate their attention according to their abilities and conditions. The framework is described by an Attention-Regulation Process and has two components: (1) Relaxation Response and (2) Attention Restoration Theory. The framework is validated by our experiment. It also informs future development for interactive meditation and has broad implications for designing mindfulness and well-being.