Extracting Psychological Indicators Using Question Answering
This is an incremental approach for researchers in psychology and NLP to analyze text for personality traits.
The paper tackled extracting psychological indicators like BIG5 traits from text by using a question-answering method with RoBERTa fine-tuned on SQuAD 2.0 and Reddit data, and results aligned with the SQuAD 2.0 benchmark, providing a baseline for future work.
In this work, we propose a method for extracting text spans that may indicate one of the BIG5 psychological traits using a question-answering task with examples that have no answer for the asked question. We utilized the RoBERTa model fine-tuned on SQuAD 2.0 dataset. The model was further fine-tuned utilizing comments from Reddit. We examined the effect of the percentage of examples with no answer in the training dataset on the overall performance. The results obtained in this study are in line with the SQuAD 2.0 benchmark and present a good baseline for further research.