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Handicapping the Oscars: Predictive Analytics Meets the Academy

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As the countdown to the annual Academy Awards ceremony ticks away, I'm seeing more and more articles in the Entertainment section of the Los Angeles Times like this one, whose aim is to predict the outcomes of the votes for the prized categories of individual performance and best picture. What all these columns have in common is the way that they are essentially using a simplified form of predictive analytics in their prognostications, aggregating data from past awards seasons to pronounce what is going to happen this time around. You know the sort of thing: if Brad Pitt wins a SAG, his Oscar's in the bag. Grab a Golden Globe, and your picture's Oscar gold. Even when the statistics aren't all that compelling (as in the seven-out-of-twenty-five correlation between winning an acting SAG and an Oscar as reported in the Times article linked to above), stats are equated with destiny, much in the same way that presidential polls are touted as sure-fire crystal balls upon the future—and you know how well that worked out in 2016.

Reliable or not, however, this preference for data over careful analysis of the relative aesthetic merits of the various contenders for the big film prizes bears cultural significance. For this is the era of BIG DATA, an age when crunching numbers fuels vast advertising, educational, and AI enterprises that not only make piles of money for those who run them but which are also, and more significantly, widely believed to hold the key to solving all our problems, including "fixing" our higher education system. (Remember how robo-grading was going to liberate—or perhaps more accurately, eradicate—writing instructors? Or MOOCS?). But no amount of disappointing results seems to dampen what is almost a religious enthusiasm for the power of aggregated data. And now this faith appears to have engulfed the traditional ritual of handicapping the Oscars.

Which leads to a second significance. Because even if the big promises of Big Data haven't exactly been met quite yet, there are serious problems that it could address (for example, it sure would be nice if the power of aggregated data could be applied to reversing global warming), but guesstimating the Oscar awards in advance isn't such a problem. So the fact that entertainment writers are employing the techniques of data-driven analytics to prognosticate who's going to win what, indicates that their readers care so much about the outcome of a ritual whereby an ultra-exclusive club celebrates itself through an annual awards ceremony which even includes a royal red-carpet treatment, that they are eager for any glimpse into the future that they can get. And in a data-driven era, it should come as no surprise that data-driven Oscar augury has become, as they say, a "thing."

Photo Credit: Pixabay Image 3679610 by analogicus, used under Pixabay License

About the Author
Jack Solomon is professor of English at California State University, Northridge, where he teaches literature, critical theory and history, and popular cultural semiotics. At present he is Director of the Office of Academic Assessment and Program Review, a task to which he frequently applies the critical thinking insights that cultural semiotics can reveal. He is often interviewed by the California media for analysis of current events and trends. He is co-author, with Sonia Maasik, of Signs of Life in the U.S.A.: Readings on Popular Culture for Writers, and California Dreams and Realities: Readings for Critical Thinkers and Writers, and is also the author of The Signs of Our Time, an introductory text to popular cultural semiotics, and Discourse and Reference in the Nuclear Age, a critique of poststructural semiotics that proposes an alternative semiotic paradigm.