Choosing research participants for Digital Research

What constitutes an appropriate or useful research participant for Digital Research? What criteria do we want our research participants to match? What even is a normal Digital user?

These are some of the questions we can often begin to ask ourselves when approaching Digital Research. What sort of participants do we want, and what makes a participant particularly useful/useless? What traits should we look for in our participants?

One potentially useful method for picking research participants is looking at the selection criteria used by other Researchers. I was encouraged to head down this path when beginning my PhD, and in particular was prodded towards the works of Robert Kozniets, a fascinating Digital Sociologist, and author of the book ‘Netnography’ (2010). In it, Kozinets lists his criteria for selecting research communities, stating that to select useful communities and collect rich and relevant data the communities ideally should be:

  • relevant to the research question
  • active, with recent and regular communication
  • interactive with a flow of data between participants
  • produce substantial data, with a large mass of communication and an energetic field
  • heterogeneous in their participants
  • data-rich.

(Kozinets 2010, p 89).

Intrigued, I attempted to apply similar criteria towards my selection of research participants, searching for participants that not only fitted the research brief, but that were active, interactive, and producers of substantial data. Buoyed on by the apparent usefulness of this approach, I started my initial interviews with the potential participants with my tick box of traits in mind, ready to see how useful the participants would be, and how much data they could produce for me. However, I quickly discovered the apparent problems with having such a rigid selection criteria for participants.

In my initial interviews, I found the participants telling me of the myriad ways they had of using the internet as a social space, of the plethora of methods, tools, and techniques at their disposal for interacting and acting online, and of the vast variety of their approaches to selecting and uploading appropriate material.  Certainly, not all of the potential participants fitted the brief. In particular, there were huge disparities in how substantive and data-rich their updates were, an how ‘active’ the participants were. Most of the participants told me of the ways they used Facebook to ‘stalk’ their friends and family, without actively engaging with them. They told me of the ways in which they considered themselves a part of a YouTube community just by watching the Videos and Vlogs of certain YouTube personalities, without actively commenting on the posts. They told me of the ways they participate Reddit communities by upvoting posts, without actively writing any posts of their own.

Certainly, they didn’t fit my initial checklist of useful traits, but should I just dismiss their usefulness as participants for Digital Research, and by dint, dismiss the usefulness of there uses of these Social Spaces in order to find participants that produced rich and plentiful data? Were any of their uses of Social Networking Sites not worthy of study and attention? Were their techniques irrelevant because they technically produced less countable and tangible data? Was their lack of substantive data a sign that they were not normal users, or was in in fact the case that they could be active participants online whilst not actively producing any data? Do the vast majority of users really produce bucket loads of data?

After initially attempting to stick to my criteria, I quickly decided that clearly a more flexible approach was needed and that, of course, their uses of these Social Spaces deserved and demanded documentation, exploration, and consideration.

In many ways, the stumbling block in selecting research participants via the tick-box criteria I adopted is the usefulness of terms such as ‘active’. What exactly does it mean to be ‘active’ online? Are we just looking for participants that produce large amounts of data for us to analyze, or should we have a broader understanding of what it means to be active within Online Social Spaces? Active certainly can be a useful term to keep in mind, but perhaps we as researchers should not be the ones to define what it means to be active online. After the first few initial interviews, I quickly shifted my approach, and instead let the participants define how they were active online. This opened up a much broader and useful understanding of online social spaces. Instead of looking for specific type of data (number of posts, images, videos etc) I found myself being told a vast array of tales and examples of the unique and fascinating techniques for acting, interacting, and engaging with and within these Online Social Spaces.

Certainly, these were not data-rich in the sense that Kozinets implies, but nonetheless, I was left with incredibly rich data.

When defining ‘activity’ online as more than just the production of data for us to collect and research, we can start to unpack and understand the vast multimodality online, we can begin to see that activity online involves a wide array of techniques and activities, from reading, clicking, and stalking to upvoting, scrolling through newsfeeds, and writing snarky responses only to delete them.

This is partly the problem with looking for specific types of data, and by dint, producers of these specific types of data; we miss what is actually happening, how the spaces are being used and interacted with, and the vast array of techniques, that don’t produce quantifiable data in the traditional sense, but that are nonetheless prevalent, interesting, and that show us much about how Online Social Spaces are interacted with and in. In the end, my decision to broaden my criteria for appropriate research participants allowed me to tick what I consider to be the most useful of Kozinets’ criteria; heterogeneity. By deciding to allow the participants to define how they were using the space, how they were interacting, and what was normality for them, I ended up with an interesting and diverse group of participant, and by dint, a glimpse into the wide array of techniques and tools for Social Interaction online, rather than potentially ending up with a group of loud, mouthy, but data-rich narcissists…

Perhaps then, we should be less rigid with criteria when entering the field and selecting participants, and instead, let the participants show us their world. Of course, we have to be practical, and their has to be a cut of point (no posts/no online presence etc) but on the whole, a looser approach to picking participants can lead to a richer understanding of how the internet is used and engaged with.

SO now, when I’m asked what I look for in a research participant for Digital Research, I answer honestly in the most annoying way possible… “…you”.

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One thought on “Choosing research participants for Digital Research

  1. Reblogged this on Harry T Dyer and commented:

    I’m just writing up the sampling section of my thesis, so I’m revisiting this now. I’m so glad I decided to allow the participants to tell me their story. As I say in the blog, the data collected may not be considered data-rich in the sense that Kozinets implies, but nonetheless, this paper was left with incredibly rich data.

    Like

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