Real time personality assessment via Big Five Traits

Personality prediction from CVs using advanced NLP is quite a significant area of interest in contemporary human resource management and recruitment processes. The study generates an innovative approach to making predictions, with textual data extracted from CVs sent for analysis regarding the Big-5 personality traits of a person. We devise a rather powerful framework to quantitatively extract subtle personality cues from unstructured text using NLP techniques, in particular transformer-based models with the incorporation of contextual embeddings. Our approach consists of CV pre-processing to extract relevant linguistic features, training sophisticated machine learning models, such as the one we use in our course, to correlate such features with personality traits, and large-scale empirical assessment to validate model accuracy. The findings reveal the potential for advanced NLP techniques in developing deep insights into the way personality profiles of candidates can be; thus, it serves as a very effective tool for improvement in recruitment processes through enhanced precision and efficiency. It would not only support informed decision-making but open further possibilities of research on the integration of personality analytics into human resource practice.