ChatGPT is the front end to a powerful large language model that has garnered widespread attention in many fields of study, including computer science (CS), where it promises to be transformational. As educators, we are just starting to grapple with the ramifications of this new technology, including implications for what we teach, how we teach, and how we grade. The decisions educators make moving forward depend heavily on the prevalence of students' use (and misuse) of ChatGPT in the classroom. Further, predictors of nefarious use could aid educators as well. We conducted an online survey to capture CS student awareness of, experience with, and attitudes toward ChatGPT. Through quantitative and qualitative analysis, we found that awareness of ChatGPT is generally high, and it is more frequently being used as a study tool than to complete students' work for them. Most students are aware of the potential for abuse in academic pursuits, but a notable minority of students admit to using it unscrupulously and to the potential for it to interfere with their learning. We conclude with a discussion of factors to consider as educators modify their approaches and develop guidelines for ChatGPT usage in their classrooms.

Following Facebook's introduction of the "Like" in 2009, CaringBridge (a nonprofit health journaling platform) implemented a "Heart" symbol as a single-click reaction affordance in 2012. In 2016, Facebook expanded its Like into a set of emotion-based reactions. In 2021, CaringBridge likewise added three new reactions: "Prayer", "Happy", and "Sad." Through user surveys (N=808) and interviews (N=13), we evaluated this product launch. Unlike Likes on mainstream social media, CaringBridge's single-click Heart was consistently interpreted as a simple, meaningful expression of acknowledgement and support. Although most users accepted the new reactions, the product launch transformed user perceptions of the feature and ignited major disagreement regarding the meanings and functions of reactions in the high stakes context of health crises. Some users found the new reactions to be useful, convenient, and reducing of caregiver burden; others felt they cause emotional harms by stripping communication of meaningful expression and authentic care. Overall, these results surface tensions for small social media platforms that need to survive amidst giants, as well as highlighting crucial trade-offs between the cognitive effort, meaningfulness, and efficiency of different forms of Computer-Mediated Communication (CMC). Our work provides three contributions to support researchers and designers in navigating these tensions: (1) empirical knowledge of how users perceived the reactions launch on CaringBridge; (2) design implications for improving health-focused CMC; and (3) concrete questions to guide future research into reactions and health-focused CMC.

We consider a variant of the art gallery problem where all guards are limited to seeing 180degree. Guards that can only see in one direction are called half-guards. We give a polynomial time approximation scheme for vertex guarding the vertices of a weakly-visible polygon with half-guards. We extend this to vertex guarding the boundary of a weakly-visible polygon with half-guards. We also show NP-hardness for vertex guarding a weakly-visible polygon with half-guards. Lastly, we show that the orientation of half-guards is critical in terrain guarding. Depending on the orientation of the half-guards, the problem is either very easy (polynomial time solvable) or very hard (NP-hard).

Online technologies offer great promise to expand models of delivery for therapeutic interventions to help users cope with increasingly common mental illnesses like anxiety and depression. For example, "cognitive reappraisal" is a skill that involves changing one's perspective on negative thoughts in order to improve one's emotional state. In this work, we present Flip*Doubt, a novel crowd-powered web application that provides users with cognitive reappraisals ("reframes") of negative thoughts. A one-month field deployment of Flip*Doubt with 13 graduate students yielded a data set of negative thoughts paired with positive reframes, as well as rich interview data about how participants interacted with the system. Through this deployment, our work contributes: (1) an in-depth qualitative understanding of how participants used a crowd-powered cognitive reappraisal system in the wild; and (2) detailed codebooks that capture informative context about negative input thoughts and reframes. Our results surface data-derived hypotheses that may help to explain what types of reframes are helpful for users, while also providing guidance to future researchers and developers interested in building collaborative systems for mental health. In our discussion, we outline implications for systems research to leverage peer training and support, as well as opportunities to integrate AI/ML-based algorithms to support the cognitive reappraisal task. (Note: This paper includes potentially triggering mentions of mental health issues and suicide.)

Online health communities offer the promise of support benefits to users, in particular because these communities enable users to find peers with similar experiences. Building mutually supportive connections between peers is a key motivation for using online health communities. However, a user's role in a community may influence the formation of peer connections. In this work, we study patterns of peer connections between two structural health roles: patient and non-professional caregiver. We examine user behavior in an online health community---CaringBridge.org---where finding peers is not explicitly supported. This context lets us use social network analysis methods to explore the growth of such connections in the wild and identify users' peer communication preferences. We investigated how connections between peers were initiated, finding that initiations are more likely between two authors who have the same role and who are close within the broader communication network. Relationships---patterns of repeated interactions---are also more likely to form and be more interactive when authors have the same role. Our results have implications for the design of systems supporting peer communication, e.g. peer-to-peer recommendation systems.

Emoji are popular in digital communication, but they are rendered differently on different viewing platforms (e.g., iOS, Android). It is unknown how many people are aware that emoji have multiple renderings, or whether they would change their emoji-bearing messages if they could see how these messages render on recipients' devices. We developed software to expose the multi-rendering nature of emoji and explored whether this increased visibility would affect how people communicate with emoji. Through a survey of 710 Twitter users who recently posted an emoji-bearing tweet, we found that at least 25% of respondents were unaware that the emoji they posted could appear differently to their followers. Additionally, after being shown how one of their tweets rendered across platforms, 20% of respondents reported that they would have edited or not sent the tweet. These statistics reflect millions of potentially regretful tweets shared per day because people cannot see emoji rendering differences across platforms. Our results motivate the development of tools that increase the visibility of emoji rendering differences across platforms, and we contribute our cross-platform emoji rendering software to facilitate this effort.

Pinterest is a popular social networking site that lets people discover, collect, and share pictures of items from the Web. Among popular social media sites, Pinterest has by far the most skewed gender distribution: women are four times more likely than men to use it. To better understand this, we examined two factors that generally affect whether people try a social site and whether they continue using it: the external perception of a site (e.g., as conveyed in popular media) and the site's initial user experience. For the latter, we focused on the role of social bootstrapping, importing contacts from one social site to another. We conducted a survey study, finding that: perceptions of Pinterest among users and non-users of the site differed significantly; trying Pinterest led to substantial changes in user perceptions of the site; social bootstrapping affected users' initial impression of Pinterest, generally improving it for women and harming it for men. We present implications of our findings for design and research.

With the rise of social networks like Facebook and Twitter, it might seem that our opportunity to communicate with others is limited only by our access to smart phones and computers. However, most social networks are not designed with complete accessibility in mind. In particular, these networks' chronological organization of news items, abundant feature sets, and busy presentation can make these tools unusable to individuals with aphasia, an acquired language disorder that compromises an individual's ability to speak, write, and recognize language. This is unfortunate, as one of the primary means of managing aphasia is to keep individuals in community. To counter this, we have developed AphasiaWeb, a social network designed exclusively for keeping individuals with aphasia and their friends and families connected. In this paper we describe the social network and share findings from a two-month trial program conducted with a local aphasia support group.