Bashar Alshouha¹, Jesus Serrano-Guerrero^1,*, Francisco Chiclana², Francisco P. Romero¹, Jose A. Olivas¹

CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 1933-1956, 2024, DOI:10.32604/cmc.2023.046711

Abstract Personality recognition plays a pivotal role when developing user-centric solutions such as recommender systems or decision support systems across various domains, including education, e-commerce, or human resources. Traditional machine learning techniques have been broadly employed for personality trait identification; nevertheless, the development of new technologies based on deep learning has led to new opportunities to improve their performance. This study focuses on the capabilities of pre-trained language models such as BERT, RoBERTa, ALBERT, ELECTRA, ERNIE, or XLNet, to deal with the task of personality recognition. These models are able to capture structural features from textual content and comprehend a multitude… More >

Yating Miao^1,2,*, Jigan Wang¹, Rundian Shen¹, Dongsheng Wang³

International Journal of Mental Health Promotion, Vol.25, No.3, pp. 357-374, 2023, DOI:10.32604/ijmhp.2023.027950

Abstract Purpose: This study investigates the effects of Big Five, HEXACO, and Dark Triad personality traits on counterproductive work behaviors (CWBs), and examines the moderating effects of countries where the studies were carried out, gender rate of samples, and scales used to measure personalities. Method: Following the rules of Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), we include 74 empirical studies published between 2007 and September 2022 with 83 samples and 394 correlations. Studies are selected from both English databases such as Web of Science and Chinese databases such as CNKI. The meta-analysis and metaregression analysis were both performed… More >

T. S. Kanchana^*, B. Smitha Evelin Zoraida

Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 2003-2013, 2023, DOI:10.32604/iasc.2023.029412

Abstract Human Facial expressions exhibits the inner personality. Evaluating the inner personality is performed through questionnaires during recruitment process. However, the evaluation through questionnaires performs less due to anxiety, and stress during interview and prediction of leadership quality becomes a challenging problem. To the above problem, Temporal sequence based SENet architecture (TSSA) is proposed for accurate evaluation of personality trait for employing the correct person for leadership position. Moreover, SENet is integration with modern architectures for performance evaluation. In Proposed TSSA, face book facial images of a particular person for a period of one month and face images collect from different… More >