And It Don't Stop
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Needed: A New Role For Criticism
A week after expressing its opposition against the launch of two new movie futures exchanges, the Motion Picture Assn. of America has assembled a coalition of entertainment industry representatives to urge the Commodity Futures Trading Commission to delay its approval of the ventures.Meanwhile, researchers at HP Labs report that they have been monitoring Twitter comments about movies and can predict box office sales with 90+ percent accuracy. They...
Do box office grosses equal popularity? Not quality, surely. What, then? America is obsessed with movie box office grosses, even though those numbers are considered bogus. By Saturday night, stories about weekend box office numbers are already washing over the web.started by monitoring movie mentions in 2.9 million tweets from 1.2 million users over three months. These included 24 movies in all, ranging from Avatar to Twilight: New Moon.
Then they took two different approaches, dealing with two very different performance metrics: the first weekend performance, which is largely built on buzz and the second weekend performance, which is largely built whether people actually like the movie.
To predict first weekend performance, they built a computer model, which factored in two variables: the rate of tweets around the release date and the number of theaters its released in. Lo and behold, that model was 97.3% accurate in predicting opening weekend box office. By contrast, the Hollywood Stock Exchange, which has been the gold standard for opening box-office predictions, had a 96.5% accuracy.
Meanwhile, to predict second-weekend performance, the authors created a ratio of positive tweets to negative ones. Then they blended that with the Tweet rate metric in another prediction algorithm. This time, the method was 94% accurate.
And reviews? Critics panned Clash of the Titans but it still grossed $60+ million on its opening weekend. More and more movies seem to be critic-proof. And movies showered in acclaim, such as Hurt Locker, can win the industry's highest honors and critical acclaim and no one sees them (after nine months in release and a starburst of Oscar glory, the film still hasn't sold more than $16 million in tickets).
Many online editors report that reviews don't pull traffic on their sites. A couple have told me that reader surveys rank reviews well below other content. Variety editors said in dropping their staff movie critics a few weeks ago that they doubted readers would notice. Sure some will. But in the current economic model, for Variety's purposes, its editors are right.
Then there's this chart from Forrester Research:
People are saying online that they would rather hear from their "friends" than critics when they're making choices about the culture and information with which they want to engage. And Washington Post media critic Howard Kurtz weighs in this morning by wondering if the days of the newspaper critic are over.
So where does all this leave reviews? And professional critics? Perhaps we need to refine the definition of the purpose/place/standing of reviews. Kurtz suggests that:
The notion that the blog culture has rendered critics redundant is ultimately an argument against specialists. And that debate stretches from the world of culture to the nature of journalism itself -- and whether its practitioners, who poke and probe on the public's behalf, have outlived their usefulness.He's wrong. It isn't an argument against specialists, it's an argument against expertise. Americans glorify the voice of the everyman, even when/if the everyman has nothing to say, or hasn't spent more than a second thinking about something. We distrust experts because they presumably "know something" the rest of us don't. Experts have lower approval ratings than Congress.
So how is it that critics and experts got such a bad rep? Partly I think it's because people think every time an expert is proven wrong on something, it's proof they should be dismissed. But infallibility is different than expertise. Is it that people aren't sophisticated enough to see the difference? I don't have an answer, but it seems a question worth pondering...
Experts inherently cut against the democratic impulse of our society. Democracy liberates, but it also levels. Experts, who by definition create a kind of hierarchy and authority, don't resonate in that kind of context.
I wouldn't bet my reputation on it, since I read the HP authors' paper for about 5 minutes, but I think the "97.3% accurate" figure is nonsense. In the paper itself, the authors *never* claim the regression model can make predictions that are "97.3% accurate" -- they claim an adjusted R-squared of 0.973, which is a different thing. That number tells you how accurate the regression model was when applied to the data the model was developed on. Using this number as a measure of accuracy is a bit like saying "I have a model that's 100% accurate because I inputted all the correct answers after the fact."