A most remarkably huge section of the Wall Street Journal was wasted today on Follow The Tweets an article by three professors who set out to attempt to predict which movie would do best at the box office based on Tweets.

Reading the article was like watching a bunch of accountants put a dollar value on “good will” in a business valuation. These three academic stooges created a “model” of course. And used LOTS of servers to store LOTS of Tweets on three movies launched on the same day.

They used Twitter’s “advanced” search feature that is “capable” of measuring whether a Tweet is good or bad based on emoticons vs . OMG!  Even our academics had to admit this is not scientific. I hung in and read on…

Their “model” was a “bit” more sophisticated. REALLY? Their model adjusted for “language” issues, as in when people are talking vacuum cleaners and Tweet “it sucks!” that would be a good Tweet. Language is nuanced and notoriously tough to measure in any quantitative fashion, and it certainly can’t be done on a broad scale (thus Twitter’s silly emoticon measurement).  How much more sophisticated could these professors’ model be beyond emoticon measurement? Not much.

They were able to successfully “predict” the biggest grossing movie – but only in retrospect, which is not really predicting is it?

Beyond the obvious problems, they’re data was purely relational, there was no way of knowing how many Tweets make a winner, just that one movie got more “positive” Tweets than the others. But it could have easily been a statistically insignificant number. And here is the kicker: the true predictive information was available within 24 hours of the first weekend release, not in Tweets, but in the box office receipts. DUH.

This only proved one thing: there are enough Tweets about movies to give three professors enough data to write something utterly inane and enough ignorant editors at the WSJ to approve the article.

For other large industries this model is hardly applicable.  Products do not launch at the same time. Not everyone who Tweets is your customer. There maybe a whole lot more people who are your customers and have very strong “predictive” feelings who NEVER Tweet.

For the rest of us, in businesses and industries outside mass appeal – that would be the vast majority of companies and small businesses – this exercise is TOTALLY useless.  We are trees falling in a Tweetless forest.  Turning to Tweets as a predictive measure is a waste of time. Meaningful interactions with our customers and prospects via the medium THEY prefer a far better use of our time.