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.

Instrumental support is critical for patients and family caregivers facing life-threatening illnesses, injuries, or chronic conditions (e.g., cancer). We partner with CaringBridge.org—a prominent online health community for journaling about health crises—to conduct a study of instrumental support in the following two phases: a content analysis of 641 journal updates; and a survey of 991 users. Quantitative results show that: (1) patients and family caregivers prefer to receive different types of support than their care networks prefer to provide; (2) people generally have more trust in their closest social connections than acquaintances or businesses to provide instrumental support; and (3) users rate “prayer support” as the most important support category to them. Building on these results, we discuss design implications to accommodate divergent preferences and to expand instrumental support networks. We also discuss the need for future work to empower family caregivers and to support spirituality, an understudied topic in HCI.

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

No abstract

No abstract

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.

No abstract

Researchers construct models of social media users to understand human behavior and deliver improved digital services. Such models use conceptual categories arranged in a taxonomy to classify unstructured user text data. In many contexts, useful taxonomies can be defined via the incorporation of qualitative findings, a mixed-methods approach that offers the ability to create qualitatively-informed user models. But operationalizing taxonomies from the themes described in qualitative work is non-trivial and has received little explicit focus. We propose a process and explore challenges bridging qualitative themes to user models, for both operationalization of themes to taxonomies and the use of these taxonomies in constructing classification models. For classification of new data, we compare common keyword-based approaches to machine learning models. We demonstrate our process through an example in the health domain, constructing two user models tracing cancer patient experience over time in an online health community. We identify patterns in the model outputs for describing the longitudinal experience of cancer patients and reflect on the use of this process in future research.