Predicting neuroticism with open-ended response using natural language processing.

ABSTRACT:

Introduction

With rapid advancements in natural language processing (NLP), predicting personality using this technology has become a significant research interest. In personality prediction, exploring appropriate questions that elicit natural language is particularly important because questions determine the context of responses. This study aimed to predict levels of neuroticism-a core psychological trait known to predict various psychological outcomes-using responses to a series of open-ended questions developed based on the five-factor model of personality. This study examined the model's accuracy and explored the influence of item content in predicting neuroticism.

Methods

A total of 425 Korean adults were recruited and responded to 18 open-ended questions about their per

SUBMITTER: Yoon S 

PROVIDER: S-EPMC11324482 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature