People often use social media platforms to seek advice about scams like ecommerce fraud or phishing; however, little research has investigated the nature of such discussion. We conducted a multi-stage thematic analysis of 1,525 posts made to four communities focused on scam discussion on Reddit, primarily from /r/Scams. We found that posters use Reddit to identify scams, discuss the strategies employed by scammers, and obtain advice on coping with victimization. The scams discussed are primarily mediated by the internet or related technologies. Users in the communities we studied especially provide informational support and reassurance to victims, although some comments reinforce victim-blaming attitudes. We also observed qualitative differences in the types of support sought and given based on the community, with the board /r/Sextortion especially being used for emotional support. We conclude that Reddit's scam discussion communities serve as a valuable resource for scam prevention and remediation. Additionally, we discuss the potential for future research and law enforcement engagement on Reddit.

Online dating services present significant privacy risks, especially for LGBTQ+ people who are "in the closet" and have not shared their LGBTQ+ identity with others. We conducted a survey (n = 114) and nine follow-up interviews with US-based, closeted users of online dating services focused on their privacy experience. We found that participants in the study were strongly concerned about the risk of being seen by social relations and institutional data sharing practices like targeted advertising. Participants experienced a range of privacy and safety harms, including inadvertent outing, unauthorized saving and sharing of photos, extortion, and harassment. To protect their privacy, participants typically limited the amount of information and the photos they included in their profile. In order to improve their privacy experience, participants requested better profile visibility controls, limits on the ability of others to download or screenshot their photos, better user verification, and making premium privacy features available for free.

Users of online services often encounter cookie banners that ask them to consent to different categories of cookies. Frequently, these categories are labelled using the four categories defined by the 2012 Cookie Guide from the UK's International Chamber of Commerce (ICC). However, prior research suggests that users have difficulty understanding what these category labels actually mean. We conducted a four-part study to identify labels that more intuitively convey the four cookie categories. First, we crowd sourced new category labels. We then evaluated users' comprehension and sentiment towards the labels in a series of surveys focused on definitions and hypothetical scenarios. Finally, we selected a new slate of category labels based on the results of the prior surveys, and conducted a between-subjects, online behavioral experiment to compare the new slate with the original labels. We ultimately recommend that the industry adopt the category label ``anonymous analytics cookies'' in lieu of the term ``performance cookies'' and ``extra functionality cookies'' instead of ``functional cookies.'' Adopting our recommended terms would both improve the usability of current cookie consent interfaces and any future privacy consent mechanisms that use the same categorization. We also recommend revisiting the categories themselves as the distinctions between these categories do not seem to be well understood and may not reflect useful distinctions for privacy decision making.

Websites implement cookie consent interfaces to obtain users’ permission to use non-essential cookies, as required by privacy regulations. We extend prior research evaluating the impact of interface design on cookie consent through an online behavioral experiment (n = 1359) in which we prompted mobile and desktop users from the UK and US to make cookie consent decisions using one of 14 interfaces implemented with the OneTrust consent management platform (CMP). We found significant effects on user behavior and sentiment for multiple explanatory variables, including more negative sentiment towards the consent process among UK participants and lower comprehension of interface information among mobile users. The design factor that had the largest effect on user behavior was the initial set of options displayed in the cookie banner. In addition to providing more evidence of the inadequacy of current cookie consent processes, our results have implications for website operators and CMPs.

Categorization via gender is omnipresent throughout society, and thus also computing; gender identity is often requested of users before they use software or web services. Despite this fact, no research has explored how software developers approach requesting gender disclosure from users. To understand how developers think about gender in software, we present an interview study with 15 software developers recruited from the freelancing platform Upwork as well as Twitter. We also collected and categorized 917 threads that contained keywords relevant to gender from programming-related sub-forums on the social media service Reddit. 16 posts that discussed approaches to gender disclosure were further analyzed. We found that while some developers have an understanding of inclusive gender options, programmers rarely consider when gender data is necessary or the way in which they request gender disclosure from users. Our findings have implications for programmers, software engineering educators, and the broader community concerned with inclusivity.