I was recently very pleased to write a few reflective comments on “Segmenting Online Communities,” the Master’s Thesis work of Hjalti Hjaltason and Marie Vernersson at Lund University in Sweden. They have undertaken in a very clear and concise manner, a study that seeks to empirically test the model of online community segments that I first proposed in an article in the European Management Journal in 1999.
That article, and the model in it, have achieved considerable popularity as a way to understand some of the different segments of online community member. The article has been cited 190 times (according to Google scholar), and the model’s quadrants and categories of the mingler, tourist, devotee, and insider are commonly featured in books, including many consumer behavior and e-commerce textbooks around the world.
Yet as Hjalti and Marie write in their introduction to this research, the article’s influential assertions and model have rarely been subject to empirical scrutiny. And that’s where this team of scholars come in.
Using a large sample (they aimed for an N=1000) of online poker players active on the Facebook, they administered a questionnaire that asked them a battery of questions about themselves and their online behaviors. For their theory-testing purposes, chief among these questions were queries that asked about their identification with the consumption practices of poker, and with their affiliation with the online community of poker players.
Their findings were quite interesting, and a bit surprising. In my 1999 article, I had speculated that, following the Pareto rule that seemed to dictate producer-like behavior in the offline world, we might expect only about 20% of online consumers to be assuming the more active, producerly roles of the devotee and the insider. However, Hjaltason and Vernersson instead found that Devotees (at a whopping 36%) and Insiders (at 25%) together account for 61% of their entire sample. Tourists (at 33%) and Minglers (at a paltry 6%) account together for a minority of online consumers, at only 39 percent.
The results themselves are interesting, and most interesting, I believe, because they open up this area to further investigation and questioning. Now, in the same interest of science, I had to ask myself why these results were so different from my own speculations. And I came up with several reasons that might assist further refinement and investigations of these topics.
First, I think that we must be very cautious about choosing field sites that are supposed to be representative of the entire phenomenon of online communities. When I originally wrote my 1999 article, almost all of my research had been based in newsgroups or bulletin boards, which were the main form of online community for over two decades, pretty much since the inception of the Internet. In those speculations of mine, I was including the many lurkers who pass by bulleting boards without ever posting on them. I think that recent research, by key people in this area like Anne Schlosser, indicate that for every person who posts, there are somewhere in the range of 50-100 (at least) who only read the posting and move along. These numbers have been repeated recently as the “Rule of 100,” “One Percent Rule,” or the pyramid, featured in a number of books about online consumer behavior like O’Connell and Huba’s Citizen Marketers.
So there are actually two anomalies to this field site. First, it is a fairly new social form, a social networking site. That makes it significantly different, in my eyes, from the newsgroups that I originally based my theory building upon. So perhaps the original theory holds for bulletins boards, but not for SNS groups. This is then boundary testing research rather than confirmatory or disconfirming research. And the confirmatory or disconfirming research is truly yet to happen.
The next anomaly has to do with the way that community is defined. It seems to be leaving out the lurkers that I explicitly sought to include when I brought in the Pareto rule (on p. 262, I state that “Boards also have wide exposure and influence, because they are perused frequently by tourists who merely lurk and do not post messages.”). So what is the universe of the online community? Is it all of those who visit? Or only those who post? Could it also be those who rate? On an SNS, could it be those who link? This sort of definitional work is important in a field as nascent as online community studies.
Another aspect of the site that makes it quite odd is that there are almost no female members, and it was composed mainly of Icelandic males (about whom I actually know very little). This seems to me to make it quite different from many of the sites I studied, such as fan sites, which had much larger female concentrations. As well, the nature of the site seemed particular. On this site, people actually were given the opportunity to go and play the game they were interested in—and thus to directly consume. Therefore, we’d expect a lot more “activity” to show up, and a logical suppression of “merely social” consuming attitudes of minglers and tourists. And this is just what we observe.
Methodologically, I take issue with the idea that self-reports reveal actual behaviors, especially those as subtle, intertwined, and complex as the various types of identifications and communications of online community members. I think that it would be interesting to see what would happen if we observed actual behaviors. All that is being measured here is the self-reports of behaviors. So if we concur that devotees and insiders are the highest status members of online communities, then people who are subject to social desirability and self-enhancement biases would be much more prone to classify themselves as devotees and insiders than as minglers or tourists. Thus, the results would overstate these two categories.
In conclusion, I’d like to say that I actually don’t know if my Pareto rule speculation will hold up to closer scrutiny. I sort of doubt it. I definitely believe that we are seeing new rules, such as the aforementioned One Percent Rule of 1% emerging to help explain some of the new phenomena were are seeing through emergent online community behaviors.
I’d also like to point other scholars to some of the other elements of the theory I proposed in that article. In particular, I speculate and link these four categories to different relational modes linked to motivational elements: the recreational, the relational, the informational, and the transformational. I also link these motivational aspects to a progression of online community involvement that transpires over time. The theory is actually quite a bit more complex than is accounted for here. It accounts both for a cross-sectional view of community membership, a motivational component, as well as a longitudinal element in which members progress through various stages, from uninvolved to more centrally involved. Well-designed, thorough studies that look deeply into these propositions would be most welcome and, I think, would be well received in the literature.
In conclusion, it has been enjoyable to read what these students have done with this model. We need more solid studies like this one to get the conversation moving about what is actually going on among all of these interesting, consumption-based online communities. We need more scholarship like this work on “Segmenting Online Communities,” by Hjalti Hjaltason and Marie Vernersson to help us to understand and really “crack the code” of online community membership and behavior.