Using Psychologically-Informed Priors for Suicide Prediction in the CLPsych 2021 Shared Task
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This paper describes our approach to theCLPsych 2021 Shared Task, in which weaimed to predict suicide attempts based onTwitter feed data. We addressed this challengeby emphasizing reliance on prior domainknowledge. We engineered novel theory drivenfeatures, and integrated prior knowledgewith empirical evidence in a principledmanner using Bayesian modeling. Whilethis theory-guided approach increases bias andlowers accuracy on the training set, it was successfulin preventing over-fitting. The modelsprovided reasonable classification accuracy onunseen test data (0.68 ≤ AUC ≤ 0.84). Ourapproach may be particularly useful in predictiontasks trained on a relatively small data set.