Techdirt. Stories filed under "forecasting"

Techdirt. Stories filed under "forecasting" Easily digestible tech news... http://www.techdirt.com/ en-us Techdirt. Stories filed under "forecasting"http://www.techdirt.com/images/td-88x31.gifhttp://www.techdirt.com/ Mon, 27 Feb 2012 17:00:00 PST DailyDirt: Build It And They Will Come... Michael Ho http://www.techdirt.com/articles/20100209/1104298096/dailydirt-build-it-they-will-come.shtml http://www.techdirt.com/articles/20100209/1104298096/dailydirt-build-it-they-will-come.shtml

Enjoy your fifteen minutes of fame, Ed Weiland -- for being a bit less surprised than most about Linsanity. Weiland wrote in 2010: "... Jeremy Lin is a good enough player to start in the NBA and possibly star." [url]

Nate Silver called himself a forecaster, explained how he looked at baseball stats, and created the PECOTA system for evaluating MLB players. Baseball Prospectus bought the PECOTA system in 2003 and publishes its forecasts for all kinds of baseball fans and fantasy baseball leagues. [url]

The annual MIT Sloan Sports Analytics Conference has picked its top ten finalists for its Research Paper of the Year. These papers discuss various stats like "15% of basketball rebounds hit the floor before being collected." [url]

To find some other online challenges and games, check out what StumbleUpon has found to play. [url]

By the way, StumbleUpon can also recommend some good Techdirt articles, too.

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]]> urls-we-dig-up http://www.techdirt.com/comment_rss.php?sid=20100209/1104298096 Tue, 6 Apr 2010 20:43:13 PDT Twitter Could Be A Good Predictor Of Box Office Sales Dennis Yang http://www.techdirt.com/articles/20100402/1618388853.shtml http://www.techdirt.com/articles/20100402/1618388853.shtml earthquake is happening. But instead of what's happening now, can it also be useful for telling what will happen in the future? Two researchers at HP Labs, Sitaram Asur and Bernardo A. Huberman, postulate that Twitter can actually be used to predict future box office results for movies. By building a computer model around the tweets for 24 movies, they claimed were able to predict the opening weekend box office results with 97.3% accuracy. An accuracy of around 97% seems unnaturally high, so I dug a little further into the actual report and found that both of these numbers were a result of combining each approach with the number of theaters associated with each release. Without taking into account the number of theaters in the release, tweets alone were able to predict at 93%. According to Asur, the correlation between theater counts alone and box office results is a paltry 39%. Considering that theater counts are probably a good indication of how well a studio thinks a film is going to perform, it seems that Hollywood should take notice of these forecasts.

The supposed gold-standard of box office predictions is Hollywood Stock Exchange, a prediction market. The researchers found that HSX had a 96.5% accuracy (when also combined with number of theaters). It's impressive that HSX gets a fair amount of accuracy despite it using "fake" currency. HSX is currently awaiting a ruling from the U.S. Commodity Futures Trading Commission that will allow it to trade using real money. When that happens, the accuracy of its prediction market should increase. At that point it may be interesting to see how much more closely the two prediction systems compare, since the apparent edge that the Twitter algorithm has right now seems too small to be significant.

In any case, with Twitter, since it's also a communications medium, tweets about a movie not only indicate interest, but also can ultimately influence a movie's sales at the box office. However, this effect seems distinctly different than the traditional notion of "observer effect," since the act of measuring the interest in a movie can actually occur without directly participating in the Twitter conversation. That said, if it becomes common practice to predict box office success by analyzing Twitter, the incentive to exploit this by spamming Twitter with tweets about an upcoming movie increases greatly. After all, the many predictions that foretold that Avatar would break box office records certainly played a self-fulfilling part in its breaking of those box office records. Furthermore, Tweets were taken for the 7 days before the weekend -- which means there would not be enough time to make any adjustment to any marketing (in the event of a dire prediction), and certainly not to production budgets, which have already been spent.

So, while, in their report, Asur and Huberman conclude:

While in this study we focused on the problem of predicting box office revenues of movies for the sake of having a clear metric of comparison with other methods, this method can be extended to a large panoply of topics, ranging from the future rating of products to agenda setting and election outcomes. 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.

The simple fact is that there is still quite a chasm to cross before Twitter can be used practically for any type of prediction or forecasting activity.

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]]> crystal-ball http://www.techdirt.com/comment_rss.php?sid=20100402/1618388853 Thu, 19 Jul 2007 08:16:43 PDT Predicting The Future Is Still Really Tough Joseph Weisenthal http://www.techdirt.com/articles/20070719/054736.shtml http://www.techdirt.com/articles/20070719/054736.shtml bold forecasts about what the future may hold. Ostensibly these forecasts are based on science or sound models, but in the end, nobody can confidently predict the future. Even those forecasts that turned out to be correct don't say too much, because the forecaster could've just been lucky. For some time, software companies have been pushing software to help make accurate predictions of future patterns, but it's not clear how effective this really is. A recent study takes issue with this technology, particularly as it relates to predicting human behavior. Although models can attempt to paint a picture of how people will behave on the aggregate (as a group), they can't say much about the actual individuals that comprise the group -- human behavior is simply too variable to be reduced to an average or a smooth bell curve. What's more, decision makers don't know how to use or understand the data that they receive, which further compounds the problem. Predictive technology will remain an interesting area of further study, but it's foolish to think we're getting to the point that we can see the future.

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