Personality Trait Detection Using Bagged SVM over BERT Word Embedding Ensembles

Understand

Recently, the automatic prediction of personality traits has received increasing attention and has emerged as a hot topic within the field of affective computing.

• In this work, we present a novel deep learning-based approach for automated personality detection from text.
• We leverage state of the art advances in natural language understanding, namely the BERT language model to extract contextualized word embeddings from textual data for automated author personality detection.
• Our primary goal is to develop a computationally efficient, high-performance personality prediction model which can be easily used by a large number of people without access to huge computation resources.