On Wikipedia, sophisticated algorithmic tools are used to assess the quality of edits and take corrective actions. However, algorithms can fail to solve the problems they were designed for if they conflict with the values of communities who use them. In this study, we take a Value-Sensitive Algorithm Design approach to understanding a community-created and -maintained machine learning-based algorithm called the Objective Revision Evaluation System (ORES)-a quality prediction system used in numerous Wikipedia applications and contexts. Five major values converged across stakeholder groups that ORES (and its dependent applications) should: (1) reduce the effort of community maintenance, (2) maintain human judgement as the final authority, (3) support differing peoples' differing workflows, (4) encourage positive engagement with diverse editor groups, and (5) establish trustworthiness of people and algorithms within the community. We reveal tensions between these values and discuss implications for future research to improve algorithms like ORES.

Expressive writing has been shown to improve physical, mental, and social health outcomes for patients struggling with difficult diagnoses. In many online health communities, writing comprises a substantial portion of the user experience, yet little work has explored how writing itself affects user engagement. This paper explores user engagement on CaringBridge, a prominent online community for writing about personal health journeys. We build a survival analysis model, defining a new set of variables that operationalize expressive writing, and comparing these effects to those of social support, which are well-known to benefit user engagement. Furthermore, we use machine learning methods to estimate that approximately one third of community members who self-identify with a cancer condition cease engagement due to literal death. Finally, we provide quantitative evidence that: (1) receiving support, expressive writing, and giving support, in decreasing magnitude of relative impact, are associated with user engagement on CaringBridge, and (2) that considering deceased sites separately in our analysis significantly shifts our interpretations of user behavior.

Spirituality is an understudied topic in social computing; however, for Online Health Community (OHC) users facing life-threatening illness, it is of fundamental importance. Through in-depth focus groups with OHC stakeholders in a US context, we derive a definition of "spiritual support" for use by designers and researchers who study online social support. We show that spiritual support is an integral dimension that underlies other social support types, and that if we ignore spirituality in design, we fail to mitigate problematic issues that arise in online spaces when users' spiritual values clash. Based on participants' ideations, we provide design implications for OHCs and other social media to better facilitate spiritual support through: (1) representing spiritual beliefs, (2) assistance with supportive communication, (3) support network visualization and mobilization, and (4) advance care planning and digital legacy.

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.

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Structured data peer production (SDPP) platforms like Wikidata play an important role in knowledge production. Compared to traditional peer production platforms like Wikipedia, Wikidata data is more structured and intended to be used by machines, not (directly) by people; end-user interactions with Wikidata often happen through intermediary "invisible machines." Given this distinction, we wanted to understand Wikidata contributor motivations and how they are affected by usage invisibility caused by the machine intermediaries. Through an inductive thematic analysis of 15 interviews, we find that: (i) Wikidata editors take on two archetypes---Architects who define the ontological infrastructure of Wikidata, and Masons who build the database through data entry and editing; (ii) the structured nature of Wikidata reveals novel editor motivations, such as an innate drive for organizational work; (iii) most Wikidata editors have little understanding of how their contributions are used, which may demotivate some. We synthesize these insights to help guide the future design of SDPP platforms in supporting the engagement of different types of editors.

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