Humans have some common traits, but when you start to design or develop any sort of program (be it government services or social software ) you start to realize that social at scale has many variations to how humans are social.
When taking that deep understanding we must understand if the trends we are seeing are the edges (or even outliers) or the norm. The common elements that cause the variation (often very large variations) are often driven by culture (as well as sub-cultures) and personality types.
Many of us who were early to blogging and many other social platforms were very much outliers and at or beyond the edges. We built and designed tools and services based on our personality types and traits. When you have 1.5 billion people the internet getting 70 million or even 200 million people that are similar to the edge case traits can be somewhat easy. What is really difficult is that next 90 percent. Keep in mind people use social tools very differently. What has worked for the very early innovators through early adopters is extremely different from the different personality types that will follow.
This gap in understanding that the world is not like us has not become real to many building social tools. But, to some it has hit hard, very hard. Much of the early Web 2.0 theories about social web patterns were looking at the edges and mistaking them for the norm. This was relatively easy to see if you have a background in social analytics and adoption trending through a society at scale.
To get beyond the edges you have to go deep, very much like danah boyd has done with her work. The work danah has done is deeply helpful as it surfaces the difference in understanding across personality types, age ranges, and many cultural influences. She deeply understood the problem that most people on line (youth and adults) were not openly social as was (and sadly still is) the common assumptions of things to come. Privacy and small groups is much more common. Today we see Facebook privacy setting with 70% or more with “Friends Only” or tighter for sharing information ([Pew’s Privacy management on social media sites” report).
This understanding the edges and norms differences is also incredibly helpful for things like gamification, which can cause really nice upticks in usage of social services with the innovator and early adopter types (in the Technology Adoption Lifecycle, that is the core of Geoffrey Moore’s Crossing the Chasm framing). But, for the rest of the users it is either non-influencial or is deeply problematic. The mix of benefit and loss is essential to understand. At IA Summit I had quite a few discussions with UX people trying to fix the communities that were damaged by gamification in the long run after a nice initial uptick. It is a tough problem and a real issue to grapple with. This is incredibly noticeable on inside the firewall communities as there is a fixed user base and you can easily see who participated and how over time and the shifts (well, you do need access to the data, which some vendors don’t provide access to).
Today many of the one year to four year old social software deployments in organizations have gone through the edge types and been finding gaps in their services and tools offered as they work to get to the norm types.
The tools must change and adapt to the edges and the norms and the two user sets don’t really work in the same way. We have a lot of seeing, thinking, understanding, and building a better path for the mainstream folks as we bring people along on this fantastic transformation those of us on the edges have been through the last 20 years and more.