Can a computer predict a literary prize?
This evening the Giller Prize winner will be announced. For those not in the know, the Giller Prize is Canada’s most prestigious literary award. Like the Man Booker in the UK or National Book Award in the US, the Giller Prize serves as a way of signalling to Canadian readers important new fiction. It relies on the judgments of experts, not markets. This is what makes literary prizes unique, but also challenging to predict (and of course fun, since the outcome is highly unknown in advance).
For the past year we have been studying what makes prizewinning novels unique when compared with novels that don’t win prizes. (Our newest paper will be available shortly). As part of that project we created a lab challenge to see if anyone in the lab was able to predict this year’s Giller Prize winner. We wanted to see how well a computer could track human judgments when it comes to literary value. Are there common traits that unite prizewinning novels?
For the purposes of the competition, we supplied students in our lab with all novels from the Giller long lists over the past two years, one sample novel from each jury member for the past two years, and then 10 years of historical data on past winners and shortlists for both the Giller Prize and 4 other literary prizes.
The rules for the competition were straightforward:
a. your algorithm has to predict both last year’s winner and this years in order to win (since you have a 1 in 12 chance of being right in any given year once the long list is announced, we thought we’d up the ante to avoid just being lucky…)
b. your predictions must be submitted before Monday, October 5, 2015, when the short list will be announced. They will be forwarded to the Dean’s Office for safe-keeping.
c. Good luck. You’ll need it 🙂
And the predictions are:
- All True Not a Lie in It by Alix Hawley
- All True Not a Lie in It by Alix Hawley
- Close to Hugh by Marina Endicott
- Outline by Rachel Cusk
- Martin John by Anakana Schofield
And the winner is…
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