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 1 to facilitate this effort.  CCS Concepts: • Human-centered computing → Empirical studies in collaborative and social computing

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.) CCS Concepts: • Human-centered computing → Empirical studies in HCI.

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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.CCS Concepts: • Human-centered computing → Empirical studies in collaborative and social computing; Empirical studies in HCI.