Investigating the Effect of Linguistic Features on Personality and Job Performance Predictions.

Personality traits are known to have a high correlation with job performance. On the other hand, there is a strong relationship between language and personality. In this paper, we presented a neural network model for inferring personality and hirability. Our model was trained only from linguistic features but achieved good results by incorporating transfer learning and multi-task learning techniques. The model improved the F1 score 5.6% point on the Hiring Recommendation label compared to previous work. The effect of different Automatic Speech Recognition systems on the performance of the models was also shown and discussed. Lastly, our analysis suggested that the model makes better judgments about hirability scores when the personality traits information is not absent.