We are trying to build a roadmap for how to do good digital ethnography of (and with) our online communities, and how to do it collectively. From the related literature we've read for our academic publication as well as some forays into replicating and expanding the methods used in Open Care, we know: this is hard. There's a reason ethnography is hard to scale, and that reason turns out to be its strength: it's deeply human, contextual, and requires commitment and immersion on the part of the ethnographer.
This brings me to my first point: to do collective ethnography, you have to be committed. Even if your job seems limited to the coding aspect of ethnographic practice, there is more to it than assigning keywords to text. It requires continuous engagement with what the community produces. To be collective, it also requires continuous engagement with fellow ethnographers -- weekly meetings with in-depth discussion about coding decisions, observations that are surfacing, challenges, and analytical implications. It requires coordination, communication, and a willingness to experience the dataset from a different researcher's perspective. Perhaps most importantly, it requires openness: about your decision-making process, when you aren't sure why you've interpreted something in a particular way, and your emotional relationship to the community's written contributions.
To facilitate this openness, we need transparent measures to understand how we are doing as we go along. We need an open codebook that we all commit to updating as we code, even though it can feel like a tedious and time-consuming process. It's worth it. And alongside this commitment, we need to have a deep respect for each others' time. Working collectively at a distance is hard. No ghosting, no long disappearances, no flimsy excuses for falling off the grid. We all know how easy it is to send an email or a message --- overall, we must commit to being honest with each other and shouldering the full weight of responsibility.
All of this requires experience. Explicit experience in both ethnographic research/writing and qualitative/ethnographic coding. As we code, and after we code, we engage in an analytical relationship to the data--- after all, we are tasked with putting into words the collective intelligence of the community. That's no small task, and it comes with responsibility. Moving between theory and practice (better -- integrating theory into coding practice, recursively) means that the final report is more than summary of main themes. It has to be! The point is to understand the kinds of arguments the community is making about their individual experiences, and what that might add up to collectively. This requires bringing diverse sources together: research on issues that the community cares about, careful and deep consideration of their stories, and a keen attention to the interactions in their comments to one another. It also requires being an active member of the community ourselves -- engaging with issues, teasing out connections, and understanding what it feels like to speak in that setting.
This also requires a commitment to learning. We aren't all going to know how to do everything. But a firm resolve to learn about what we don't know is an absolute requirement.
These are a few of my thoughts on what's important--- I'd love to hear from others as well.