Deep in our underground hollowed-out volcanic lair, ninja scientists have developed an algorithm that I think will have a large impact on both science and commerce. We call it "Social Value."
Social Value is the amount of behavior that one person generates among their friends. An anology might be the ripple on the social pond. Let's say this person goes to see a movie, listens to a song, or plays a game. Now let's say that this person is influential. How much more likely are their friends to go see the movie, hear the song, or play the game?
Each person has a unique amount of influence in their social network, and on each friend. Maybe you are highly influential on Bob, but Steve doesn't care what you do. What the Social Value algorithm does is to add up all of your influence and put it in units we care about--like sessions, time, or dollars.
Now imagine that we also have a good sense of the person's own future behaviors, thanks to some predictive modeling. This means that for any one person, we're generating two values:1) An asocial, future behavior number. Marketers call this lifetime value (LTV), but they don't strip out the social impact. This approach does.
2) Social value. An amount, independent of the product, service or activity (i.e. independent of the movie, song or game), caused by the social connections of the person.
Put together and viewed in the aggregate, these values show how much behavior is attributable to the service, and how much is attributable to the community around the service. We're finding that the typical split is about 75/25, where 25c on the dollar is due to community, rather than the product. This number goes up when there's robust community, and down when there isn't.
In gaming, we're seeing a 10-40% range for Social Value.
Knowing these numbers and who they are attached to has a strong and clear value proposition for the developers--find the high Social Value people and a) get more of them, b) retain them, & c) leverage them to cause others to spend more. People with big Social Value numbers can be thought of as "Social Whales."
Conversely--and this I hope to blog on in the future with some shareable data--there's a fun side effect of the scores when a person has a negative Social Value. That's a person who's presence in the network depresses the activity of others. The scientific term is "asshole," or in the game context, troll. I'm looking forward to seeing how firms use this number.
So, that's the commercial side of things. On the research side, I think this algorithm has a lot of applicability in the social sciences. After all, it doesn't care what the behavior is--voting, shopping, writing, singing, whatever.
Inspired by Mark Chen's project summary and ensuing discussion, I have been thinking that we should collect on our collective experience and document some of the ways we achieve insight in an area as rapidly evolving as virtuality. In the associated comment thread, Richard and I discuss method, and I explain a lot more about participant observation and why it is sometimes ok to be subjective. We have also had more than a few discussions about method over the years.
That said, it's still a highly emergent and tricky area, with researchers and practioners inventing and reinventing methods on a constant basis. This, arguably, is a good thing.
In my MMO research I made a lot of methodological decisions based on technological parameters/ limitations (WoW, for instance, didn't have an easy way of collecting chats, yet City of Heroes did - critical to my method that I can collect qual data such as this, therefore it had to be CoH). What are the rules? Is it a spectrum inclusive of scholarly and commercial efforts accompanied by a range of expectations about what constitutes evidence, truth, and calls to action?
A lateral thought: I have also been pleasantly surprised to see more and more speculative ideas about virtual worlds, virtual life, the virtual sel(ves), etc. etc. etc. (even entire tv series). I appreciate the big picture perspective: what got us here, and where we might be going. I'm also involved in some projects that remind me how far we've come, and how much further we have to go.
Of course, history tells us that we tend to overestimate some of technology's impacts while simultaneously overlooking others (Alan Kay?). My role as an anthropologist encourages me to look around me and try to ascertain what aspects of our culture are likely to survive, to morph, what technologies are emerging, what sub-cultures will thrive, what people will care about, how they will play/work, how kinship and learning and philosophy change, or don't. Etc. Really not a lot of crystal ball gazing, just observation coupled with intuition and a deep embedding in the culture(s) in question. We even accept anecdotes in this 'verse.
My role as a futurist attempts to project what our world might look like within that context, or better yet, within some variations not even imagined, or imaginable. In a usability lab, I might take advantage of specfic data collection methods that prove a point in graphs and charts of what happened in that one session on that day. Extrapolation is, of course, possible, but not 100% accurate, once observer effects, natural vs artifical environments and longer term behaviors are evaluated. However, there are seeds of some possible future(s) in these observations. The question, ultimately, is what will stick, and what will fade. Or as an old friend called William Shakespeare said:
If you can look into the seeds of time and say, which grain will grow, and which will not, speak then to me.
Tricky business. 'If Union Pacific had realized they were in the transportation business, instead of the railroad business, we'd be flying on Union Pacific planes'. (someone said it). Decoupling technologies from cultural shifts is the first step in understanding. Or at least that's my opinion and my preferred approach, which is really only a variation in perspective, not better or worse than other approaches, but pieces of the puzzle.
Above I have commented on some of the methods I use in achieving a deeper understanding of virtuality. I know psychology, law, economics, education, cybernetics, cultural theory and communications have yet other perspectives, while commercial research's distance between, say, market research and observational player research, is often a cultural chasm that doesn't take advantage of those perspectives in symbiosis. Yet it achieves other things, so in combination with other approaches, it becomes a way of observing in details some facets of the overall possibility/problem space to be explored. Different types of data persuade different categories of stakeholders, eliciting the change(s) desired. A constellation of methods can better assure success (inspiring relevant change/innovation) in the distributed, interdisciplinary groups we work within.
Soon I will post a more thorough introduction to my preferred approaches, one of which is cyborg anthropology (if you just can't wait, you can buy the book or hear Amber Case explain it...). In the meantime, Marshall McLuhan:
“We become what we behold. We shape our tools and then our tools shape us.”