Computational techniques offer a means to overcome the amplified complexity and resource-intensity of qualitative research on online communities. However, we lack an understanding of how these techniques are integrated by researchers in practice, and how to address concerns about researcher agency in the qualitative research process. To explore this gap, we deployed the Computational Thematic Analysis Toolkit to a team of public health researchers, and compared their analysis to a team working with traditional tools and methods. Each team independently conducted a thematic analysis of a corpus of comments from Canadian news sites to understand discourses around vaccine hesitancy. We then compared the analyses to investigate how computational techniques may have influenced their research process and outcomes. We found that the toolkit provided access to advanced computational techniques for researchers without programming expertise, facilitated their interaction and interpretation of the data, but also found that it influenced how they approached their thematic analysis.

Recovery from addiction is a journey that requires a lifetime of support from a strong network of peers. Many people seek out this support through online communities, like those on Reddit. However, as these communities developed outside of existing aid groups and medical practice, it is unclear how they enable recovery. Their scale also limits researchers’ ability to engage through traditional qualitative research methods. To study these groups, we performed a topic-guided thematic analysis that used machine-generated topic models to purposively sample from two recovery subreddits: r/stopdrinking and r/OpiatesRecovery. We show that these communities provide access to an experienced and accessible support group whose discussions include consequences, reflections, and celebrations, but that also play a distinct metacommunicative role in supporting formal treatment. We discuss how these communities can act as knowledge sources to improve in-person recovery support and medical practice, and how computational techniques can enable HCI researchers to study communities at scale.

As online communities have grown, Computational Social Science has rapidly developed new techniques to study them. However, these techniques require researchers to become experts in a wide variety of tools in addition to qualitative and computational research methods. Studying online communities also requires researchers to constantly navigate highly contextual ethical and transparency considerations when engaging with data, such as respecting their members' privacy when discussing sensitive or stigmatized topics. To overcome these challenges, we developed the Computational Thematic Analysis Toolkit, a modular software package that supports analysis of online communities by combining aspects of reflexive thematic analysis with computational techniques. Our toolkit demonstrates how common analysis tasks like data collection, cleaning and filtering, modelling and sampling, and coding can be implemented within a single visual interface, and how that interface can encourage researchers to manage ethical and transparency considerations throughout their research process.

Human-Computer Interaction researchers have explored how online communities can be leveraged for peer support, but general disinterest and a lack of engagement have emerged as substantial barriers to their use in practice. To address this gap, we designed Merlynne, a serious game that seeks to motivate individuals to support peers through Cognitive Behavioural Therapy (CBT). Our game explored use of the Proteus Effect - a phenomenon where players adopt characteristics of their in-game avatar - to motivate peer support through stereotyped 'helpful' and 'unhelpful' avatars. We then conducted a mixed-methods, exploratory study to investigate its design. We found that our game successfully motivated players to offer peer support, despite the substantial emotional labour required by CBT. However, we were not able to replicate the Proteus Effect, and did not find differences in that support based on a player's avatar. In reflecting on our findings, we discuss design challenges and considerations for the use of serious games to motivate participation in mental health support, including: fatigue, a player's need for self-expression and to relate to those they are supporting, and ludonarrative dissonance.