In the first paper I’ve seen using social media (like Twitter) to tie to a real world monetary outcome, Asur and Huberman (2010) at the Social Computing Labs in Palo Alto, CA use Twitter activity to predict film box office sales. Taking all 24 major film releases between November 2009 and January 2010, the number of tweets on new films predict sales even better than the Hollywood Stock Exchange (HSX), an online prediction game (think fantasy football for film success) that is described as the “gold standard” for predicting box office revenues.
Especially amazing is just how powerful this prediction model is – the adjusted R^2 predicting first weekend box office sales from average number of tweets per hour is 0.80. That’s amazingly high – in other words, 80% of the variability in box office sales can be explained by variability in tweets. And that’s a relatively simple metric!
When examining this pattern over time and including the number of theaters that the movie is released in, that number jumps to 97.3%, which is slightly better than the 96.5% achieved by HSX ratings plus number of theaters. Keep in mind that the HSX is filled with people explicitly trying to predict film success, while the Twitter method uses only observed chatter. That’s a powerful tool.
The problem moving forward, of course, is that 1) if Twitter is used to predict film success, 2) more people will pay attention to Twitter as an indicator of whether or not to see a movie, 3) the film industry will begin even more aggressive viral/covert marketing strategies using these technologies, and 4) the value of this measurement system decreases. But for now… it’s certainly an impressive find. The authors comment:
At a deeper level, this work shows how social media expresses a collective wisdom which, when properly tapped, can yield an extremely powerful and accurate indicator of future outcomes.
That might be a little generous, but it does lead me to wonder – what other organizational outcomes could we predict?
Several stories have appeared recently discussing efforts to blur the line between reality and the virtual.
First, in a presentation at IEEE Haptics Symposium, we have the haptic gaming vest, a wearable gaming accessory that simulates gunshots in the front and back of your chest in Half-Life 2. If you get shot in the back, you’ll feel two solenoids punch you in the back. If you sliced with a knife, you’ll feel a sudden rough vibration in your shoulders. Users described the sensation with a range of reactions, apparently dependent on how tightly the vest was fitted.
Second, a multidisciplinary team unveiled a new technology that can convert thoughts to text, called the Mind Speller. The technology is based on the electroencephalogram (EEG), which monitors brain activity through a cap with electrodes placed at strategic locations around the head. Such general technology already exists in various forms, but the big advantage to the new system is its ease of portability – so portable, in fact, that a dry version is under development. If you’re unfamiliar with EEGs, traditionally a gel must be applied to your head between the cap and your skin in order to create the best connection for monitoring brain activity, which is quite inconvenient. If a simple cap can be fit on the head without any gel, the number of applications for this kind of technology increase dramatically – just imagine a video game or training program driven by thought alone.
Finally, despite all this promising technology, at least one journalist laments the goal of modern games to reach toward realism, saying:
We miss out on some of the great potential of this medium if we focus too heavily on the real. We have the power to create entire worlds—isn’t using this power to create a shadow of reality a bit of a cop-out? And really, it’s only a conceptual cop-out. In practice, reality is quite hard to recreate. This is why the lushly-detailed world of Avatar’s Pandora is so compelling to people. It’s new, but recognizable. It’s compellingly different, but not alienating. This is the potential that exists within games.
Good or bad, these reveals are all certainly interesting. I for one am very excited about the potential for business and military applications made possible by these sort of integrations. I’ve never hidden my fascination with the possibilities of augmented reality for training, and this is the same basic idea.
Just imagine how memorable military training would be where getting shot in the simulator gave you a real physical reminder that you could have been dead in the real world.
A recent article in Newsweek discussed the use of online games like Farmville and virtual worlds like Second Life for studying human behavior when buying and selling goods, a field called behavioral economics. Consider the power of this experimental design:
Instead of dealing only with historical data, in virtual worlds “you have the power to experiment in real time,” Segerstrale says. What happens to demand if you add a 5 percent tax to a product? What if you apply a 5 percent tax to one half of a group and a 7 percent tax to the other half? “You can conduct any experiment you want,” he says. “You might discover that women over 35 have a higher tolerance to a tax than males aged 15 to 20—stuff that’s just not possible to discover in the real world.”
While that certainly sounds attractive, I have to wonder just how representative buyers of virtual goods are of the population at large. Is the woman over 35 with higher tolerance to tax buying virtual designer clothing from the same population as the woman over 35 buying clothing at Old Navy and Gap?
It’s also important to note that online economies are typically based on microtransactions. For those of you not familiar with microtransactions, they are exactly as they sound – buying and selling for very small amounts of money, often in a virtual currency.
As an example, consider a virtual artist’s easel that I sell through the XStreet SL marketplace for use in Second Life.
It costs me nothing ($0) to produce these easels. It originally took me about 20 minutes to physically design it in SL.
It costs a buyer L$50 (US$0.20) to purchase a copy of the easel.
I lose L$2 (US$0.01) in fees for selling the easel on XStreet SL.
I only sell 4 or 5 of these per month, resulting in a total monthly profit for me on this item of roughly L$200-250 (US$0.80 – US$1.00). If XStreet SL raised its fee rate from 4% to 7%, I wouldn’t really care, because it’s just not that much money to begin with.
But wait, you say – what about people who spend a lot on virtual goods? You know someone that spends $50 per month on virtual clothing? Because that behavior is relatively unusual, I’d argue that this just means the representativeness problem is even more of a concern.
So either way, there’s trouble, and it causes me to question results from such studies. Either you study everyone and risk including people with spending motivations dissimilar to the real world, or you only study the big spenders and risk excluding all the “normal” purchasers. Is there a middle ground? Not one that I can see.