Personality Trait Detection via Transfer Learning

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.Tra-ditional 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 of language facets and complex features such as hierarchical relationships or long-term dependencies.This makes them suitable to classify multi-label personality traits from reviews while mitigating computational costs.The focus of this approach centers on developing an architecture based on different layers able to capture the semantic context and structural features from texts.Moreover,it is able to fine-tune the previous models using the MyPersonality dataset,which comprises 9,917 status updates contributed by 250 Facebook users.These status updates are categorized according to the well-known Big Five personality model,setting the stage for a comprehensive exploration of personality traits.To test the proposal,a set of experiments have been performed using different metrics such as the exact match ratio,hamming loss,zero-one-loss,precision,recall,F1-score,and weighted averages.The results reveal ERNIE is the top-performing model,achieving an exact match ratio of 72.32%,an accuracy rate of 87.17%,and 84.41%of F1-score.The findings demonstrate that the tested models substantially outperform other state-of-the-art studies,enhancing the accuracy by at least 3%and confirming them as powerful tools for personality recognition.These findings represent substantial advancements in personality recognition,making them appropriate for the development of user-centric applications.

The Impact of Big Five Personality Traits on Older Europeans’ Physical Health

Investigating the role of Big Five personality traits in relation to various health outcomes has been extensively studied. The impact of “Big Five” on physical health is here explored for older Europeans with a focus on examining age groups differences. The study sample included 378,500 respondents derived from the seventh data wave of Survey of Health, Aging and Retirement in Europe (SHARE). The physical health status of older Europeans was estimated by constructing an index considering the combined effect of well-established health indicators such as the number of chronic diseases, mobility limitations, limitations with basic and instrumental activities of daily living, and self-perceived health. This index was used for an overall physical health assessment, for which the higher the score for an individual, the worst health level. Then, through a dichotomization process applied to the retrieved Principal Component Analysis scores, a two-group discrimination (good or bad health status) of SHARE participants was obtained as regards their physical health condition, allowing for further con-structing logistic regression models to assess the predictive significance of “Big Five” and their protective role for physical health. Results showed that neuroti-cism was the most significant predictor of physical health for all age groups un-der consideration, while extraversion, agreeableness and openness were not found to significantly affect the self-reported physical health levels of midlife adults aged 50 up to 64. Older adults aged 65 up to 79 were more prone to open-ness, whereas the oldest old individuals aged 80 up to 105 were mainly affected by openness and conscientiousness. .

Model considering panic emotion and personality traits for crowd evacuation

Panic is a common emotion when pedestrians are in danger during the actual evacuation, which can affect pedestrians a lot and may lead to fatalities as people are crushed or trampled. However, the systematic studies and quantitative analysis of evacuation panic, such as panic behaviors, panic evolution, and the stress responses of pedestrians with different personality traits to panic emotion are still rare. Here, combined with the theories of OCEAN(openness, conscientiousness,extroversion, agreeableness, neuroticism) model and SIS(susceptible, infected, susceptible) model, an extended cellular automata model is established by the floor field method in order to investigate the dynamics of panic emotion in the crowd and dynamics of pedestrians affected by emotion. In the model, pedestrians are divided into stable pedestrians and sensitive pedestrians according to their different personality traits in response to emotion, and their emotional state can be normal or panic. Besides, emotion contagion, emotion decay, and the influence of emotion on pedestrian movement decision-making are also considered. The simulation results show that evacuation efficiency will be reduced, for panic pedestrians may act maladaptive behaviors, thereby making the crowd more chaotic. The results further suggest that improving pedestrian psychological ability and raising the standard of management can effectively increase evacuation efficiency. And it is necessary to reduce the panic level of group as soon as possible at the beginning of evacuation. We hope this research could provide a new method to analyze crowd evacuation in panic situations.

An analysis of association of personality traits with job burnout among nurses working in hospital

Objective:The objective of the present study is to explore the effects of personality traits on job burnout among hospital nurses.Materials and Methods:This cross-sectional research was done during 2019-2020 at Kashan Shahid Beheshti Hospital.The data analysis procedures included descriptive statistics and the partial least squares-based structural equation modeling.The participants were 150 nursing professionals.A questionnaire indicating information on demographics,burnout(measured using the Maslach Burnout Inventory with three dimensions of depersonalization,emotional exhaustion,and personal accomplishment),and personality profile(measured employing the neuroticism extraversion openness five-factor inventory including extroversion,conscientiousness,agreeableness,neuroticism,and openness to experience dimensions)was used to gather the required data.Results:The results of the study showed that the validity and reliability of the measurement model were desirable(factor load higher than 0.5,the Cronbach’s alpha value and the composite reliability are>0.7).Structural model showed statistically drastic,negative relationship between the nurses’burnout levels and neuroticism(β=0.722)and openness to experience(β=0.437).However,the relationship was significantly positive between the nurses’burnout levels and conscientiousness(β=0.672),agreement(β=0.594),and extraversion(β=0.559)(P<0.03).Conclusions:The present study helped the recognition of burnout among nurses working in hospitals and approved the effects of personality features on the burnout experience.

Personality Traits, Thinking Styles, and Emotional Intelligence in Nursing, towards Healthcare Providers’ Characterization and Safer Patient Care

Background: This study explored nursing personality traits (Big Five Inventory BFI), emotional intelligence (EI), and thinking styles (Rational, RS, and Experiential, ES) together with demographic data to see how they could relate and the implication of this on nurses and patient safety. Design: A cross-sectional study. Methods: Nursing sample (n = 435). Participants completed a self-report online survey, which included demographic information, followed by questionnaires to measure personality traits, thinking styles, and emotional intelligence. Results: Spearman’s rank correlation was computed to assess the relationship between EI and Extraversion;there was a moderate positive correlation between the two variables, r = 0.487, p r = 0.731, p r = 0.723, p r = -0.666, p r = 0.467, p Conclusion: Different studies consolidated each other, and all converge and channel into the concept of characterization of healthcare providers for better support to them and safer patient care. EI correlated with all BFI components, and both positively impacted all desirable behaviors. Therefore, it would be valuable if organizations invested in increasing EI in their providers as it might highlight areas for improvement and equip providers with appropriate and advantageous coping strategies.

Understanding Nonverbal Communication Cues of Human Personality Traits in Human-Robot Interaction

With the increasing presence of robots in our daily life,there is a strong need and demand for the strategies to acquire a high quality interaction between robots and users by enabling robots to understand users’mood,intention,and other aspects.During human-human interaction,personality traits have an important influence on human behavior,decision,mood,and many others.Therefore,we propose an efficient computational framework to endow the robot with the capability of understanding the user’s personality traits based on the user’s nonverbal communication cues represented by three visual features including the head motion,gaze,and body motion energy,and three vocal features including voice pitch,voice energy,and mel-frequency cepstral coefficient(MFCC).We used the Pepper robot in this study as a communication robot to interact with each participant by asking questions,and meanwhile,the robot extracts the nonverbal features from each participant’s habitual behavior using its on-board sensors.On the other hand,each participant’s personality traits are evaluated with a questionnaire.We then train the ridge regression and linear support vector machine(SVM)classifiers using the nonverbal features and personality trait labels from a questionnaire and evaluate the performance of the classifiers.We have verified the validity of the proposed models that showed promising binary classification performance on recognizing each of the Big Five personality traits of the participants based on individual differences in nonverbal communication cues.

Personality traits and self-harm behaviors among Chinese children and adolescents: The mediating effect of psychological resilience

BACKGROUND Previous studies have shown that personality traits are associated with self-harm(SH)in adolescents.However,the role of resilience in this association remains unclear.Our research aims to explore the hypothesized mediation effect of resilience in the relationship between personality traits and SH in Chinese children and adolescents.AIM To evaluate resilience as a mediator of the association between personality traits and SH.METHODS A population-based cross-sectional survey involving 4471 children and adolescents in Yunnan province in southwestern China was carried out.Relevant data were collected by self-reporting questionnaires.Univariate and multivariate logistic regression models were employed to identify associated factors of SH.A path model was used to assess the mediation effect of resilience with respect to personality traits and SH association.RESULTS Among the 4471 subjects,1795 reported SH,with a prevalence of 40.1%(95%CI:34.4%-46.0%).All dimensions of personality traits were significantly associated with SH prevalence.Resilience significantly mediated the associations between three dimensions of personality(extroversion,neuroticism,psychoticism)and SH,accounting for 21.5%,4.53%,and 9.65%,respectively,of the total associations.Among all dimensions of resilience,only emotional regulation played a significant mediation role.CONCLUSION The results of the study suggest that improving emotion regulation ability might be effective in preventing personality-associated SH among Chinese children and adolescents.

Relationship of Smartphone Dependence to General Health Status and Personality Traits among University Students

We investigated associations between smartphone dependence and general health status or personality traits. To 197 medical university students, we administered a set of self-reporting questionnaires designed to evaluate these parameters. For males, smartphone dependence positively correlated with somatic symptoms, anxiety and insomnia, and emotional instability, and negatively correlated with agreeableness. For females, smartphone dependence positively correlated with somatic symptoms, severe depression, and extraversion, and negatively correlated with social dysfunction. These findings suggest that smartphone dependence may be associated with general health status or personality traits and that there may be a gender difference in these associations.

The Correlation between Synthetic Oxytocin Given during Labor and Women’s Personality Traits According to the SSP (Swedish University Scales of Personality) Survey: A Pilot Study

Background: In modern obstetric care, oxytocin is one of the most frequently used drugs, and the possible mental impact this drug has on women is very little studied. The objective of this study is to investigate whether women augmented with oxytocin during labor will rate their personality profile differently after childbirth than non-stimulated women. Methods: Prospective cohort study was performed at Women’s Clinic, Soder hospital, Stockholm.76 women received the SSP (Swedish University Scales of Personality) questionnaire to fill in during their stay in the post-maternity ward after labor. Information about the use of oxytocin was retrieved from the women’s medical records. Primary outcome: Differences in the SSP scores in the group augmented with synthetic oxytocin during labor compared with the non-augmented group. Results: Women with and without oxytocin estimates on the SSP subscale form differed regarding personality traits described as “lack of assertiveness” (p = 0.04), which means “lack of ability to speak up and to be self-assertive in social situations”. The result also showed that women that had a long time of augmentation with oxytocin (>5 h) scored higher for “social desirability” (p = 0.004), which was defined as being “socially adapted,” “friendly,” and “helpful”. A difference in “psychological anxiety” (p = 0.04) and “social desirability” (p = 0.004) was found among women who had oxytocin in a dose of at least 200 ImU/h for ≥1 hour. This group also had a lower rate of “mental anxiety” than those who received lower oxytocin doses. Conclusion: Synthetic oxytocin given during labor may affect the woman mentally. The total time and volume of given oxytocin seem to be essential factors when discussing augmentation’s maternal psychological response. We conclude that prolonged and extended use of synthetic oxytocin during labor should be avoided if possible.

Relationship between Sexual Fantasy,Sexual Communication,Personality Traits and Sexual Satisfaction in Married Individuals

The study aimed to understand the relationship between sexual fantasy,sexual communication,personality traits and sexual satisfaction in married individuals.Sexual fantasy as a variable has seldom been studied in the Indian context.The importance of sexual fantasies has been noted by therapists and researchers.Studying various aspects of sexual functioning in married life including,sexual communication and sexual satisfaction and personality traits would be beneficial.A cross sectional design with a total sample of 100 married individuals was considered.Tools were administered as online forms.Parametric and Non-parametric tests were used to find the correlation between Sexual fantasy and sexual satisfaction,sexual communication and sexual satisfaction and personality traits and sexual satisfaction.Results indicated that sexual fantasy and sexual satisfaction have a negative correlation,sexual communication and sexual satisfaction have a positive correlation and personality traits and sexual satisfaction also have a positive correlation.This study can be used to develop modules that might aid in marital and sex therapy.It may be useful in identifying any difficulties or issues which may help in providing appropriate timely intervention.

Who Are You Meant to Be? Predicting Psychological Indicators and Occupations based on Personality Traits

Recognition of psychological characteristics based on massive data and computer machine learning algorithms has gradually become a new way for psychological research. As we all know, person-job fit is an important consideration in recruitment and selection. Most existing selection process can reliably measure skills fit, i.e., matching job seekers’ skills/work experience with job demand. What is often harder to assess is the compatibility between job seekers’ motivational needs/career aspirations and job characteristics, which will ultimately determine their career progress and job satisfaction. With the increasing application of machine learning methods in psychology, this paper constructed classification models to predict individuals’ needs, career aspiration, and occupation through their personality traits. This enables automatic access to individuals’ psychological indicators, with the MLP (Multi-Layer Perceptron) method showing the highest prediction accuracy. In addition, it conducted a comparative analysis of the distribution of personality characteristics in different occupations. Based on the study results, we put forward some countermeasures and suggestions for application in human resource management.

Is tax evasion macho?Testosterone,personality traits and evasion

This paper examines the potential effects of testosterone and personality traits on the decision to evade taxes.In a series of experiments,subjects completed behavioural tasks and made a one-shot tax evasion decision.We estimate a negative weakly significant treatment effect,which suggests that an exogenous increase in the testosterone level may inhibit the decision to evade taxes.Our results also suggest that higher dominance and independent self-construal,as well as lower self-control,are associated with a greater likelihood of tax evasion.We discuss the mechanisms potentially linking testosterone to tax evasion.These findings support the inclusion of biological factors in the analysis of tax evasion behaviour.

Physiognomy： Personality Traits Prediction by Learning

Evaluating individuals＇ personality traits and intelligence from their faces plays a crucial role in interpersonal relationship and important social events such as elections and court sentences. To assess the possible correlations between personality traits （also measured intelligence） and face images, we first construct a dataset consisting of face photographs, personality measurements, and intelligence measurements. Then, we build an end-to-end convolutional neural network for prediction of personality traits and intelligence to investigate whether self-reported personality traits and intelligence can be predicted reliably from a face image. To our knowledge, it is the first work where deep learning is applied to this problem. Experimental results show the following three points： 1） ＂Rule-consciousness＂ and ＂Tension＂ can be reliably predicted from face images. 2） It is difficult, if not impossible, to predict intelligence from face images, a finding in accord with previous studies. 3） Convolutional neural network （CNN） features outperform traditional handcrafted features in predicting traits.

Personality Assessment Based on Natural Stream of Thoughts Empowered with Machine Learning

Knowing each other is obligatory in a multi-agent collaborative environment.Collaborators may develop the desired know-how of each other in various aspects such as habits,job roles,status,and behaviors.Among different distinguishing characteristics related to a person,personality traits are an effective predictive tool for an individual’s behavioral pattern.It has been observed that when people are asked to share their details through questionnaires,they intentionally or unintentionally become biased.They knowingly or unknowingly provide enough information in much-unbiased comportment in open writing about themselves.Such writings can effectively assess an individual’s personality traits that may yield enormous possibilities for applications such as forensic departments,job interviews,mental health diagnoses,etc.Stream of consciousness,collected by James Pennbaker and Laura King,is one such way of writing,referring to a narrative technique where the emotions and thoughts of the writer are presented in a way that brings the reader to the fluid through the mental states of the narrator.More-over,computationally,various attempts have been made in an individual’s personality traits assessment through deep learning algorithms;however,the effectiveness and reliability of results vary with varying word embedding techniques.This article proposes an empirical approach to assessing personality by applying convolutional networks to text documents.Bidirectional Encoder Representations from Transformers(BERT)word embedding technique is used for word vector generation to enhance the contextual meanings.

The Relationship between Mental Disorders and Personality of Outpatients in a Psychiatric Clinic in Nanjing, China

Psychosis has increasingly become a social problem,emphasizing the need to understand the relationship between mental disorders and personality.This study aimed to investigate the relationship between mental disorders and personality among psychiatric outpatients based on real-world data.Symptom Checklist 90(SCL-90)and Eysenck Personality Questionnaire(EPQ)were used to evaluate the personality and psychopathological symptoms of patients(n=8409)in the Psychiatric Outpatient Department at Nanjing Drum Tower Hospital.t-test was used to compare scores between patients and national norms.Pearson’s correlation coefficient and path analysis were used to explore the relationship between mental health status and personality.The correlation coefficient between the neuroticism(N)score and each factor score of the SCL-90 test,as well as the correlation between psychoticism(P)and hostility and paranoia,exceeded 0.4.Path analysis revealed that the standardized path coefficients of N score and SCL-90 were all higher than 0.4.In addition,the standardized path coefficient of hostility and paranoia on P score were 0.313 and 0.280,respectively.Interpersonal sensitivity,depression and obsessive-compulsive symptoms were affected by extraversion(E)score,with standardized path coefficients of-0.149,-0.138,and-0.105,respectively.The path analysis also showed the direct and indirect effects of age,gender,education,and marital status on SCL-90.Patients characterized as melancholic had higher scores in all factors of SCL-90.In conclusion,mental health was related to personality traits of neuroticism,psychoticism and introversion.

The Role of Trait Activation Theory in Occupational Behavior:A Systematic Review

The Trait Activation Theory(TAT)is widely regarded as the most influential personality theory approach in psychology.The purpose of this study is to analyze the TAT’s role in the contemporary workplace.Which personality traits are more likely to predict work success?Which characteristics should businesses prioritize throughout the recruiting and selection processes?According to the Trait Activation Theory,what is the significance of motivation in the workplace and how can employers find employees who can be more productive,efficient,and involved in the organization’s goals?A systematic review of past recent research was used to answer the questions raised above.Following the gathering and examination of multiple recent publications on the issue,it was determined that the use of this model had a favorable impact on individual and group performance,working relationships,manager job performance,and workplace creativity.

Who Benefits More from Physical Exercise?On the Relations between Personality,Physical Exercise,and Well-Being

Although employers believe that encouraging and supporting physical exercise activities by purchasing fitness equipment and building sports venues can improve employees’well-being,the utilization rate is rather low.Since most of the evidence of the well-being promotion in the workplace concentrated on the perspectives of organizational factors and psychosocial factors and focused on the reduction of the negative affect of well-being,it is still an open question whether physical exercise has benefits on both negative and positive affect of well-being and who benefits more from physical exercise.Thus,the purpose of this study is to investigate the impact of physical exercise on occupational well-being(job burnout and work engagement)and examine whether effectiveness depends on personality traits.Online questionnaires were distributed.The sample included 671 participants from different enterprises in China.Results showed that the effectiveness of physical exercise was also applicable to well-being in the workplace.Physical exercise was negatively correlated with job burnout and positively correlated with work engagement.The effectiveness was different among employees with different personality traits.Contrary to our expectation,individuals with neuroticism were more likely to improve their work engagement through physical exercise.Extroversion and conscientiousness weakened the benefits of physical exercise.Therefore,differences of effectiveness among different personality traits emphasize the need for a more personalized strategy in physical exercise interventions.

Determinants of Satisfaction at Work and Its Reflections on Performance

This study examines the relationship between job satisfaction and performance,investigating personality traits and satisfaction aspects among employees of a Federal Higher Education Institution.A questionnaire was administered to 658 participants,using structural equation modeling for analysis.Results highlighted that challenging work,neuroticism,and self-esteem significantly influenced overall workplace satisfaction,while general satisfaction,self-efficacy,and lack of attention were key determinants of work performance.This emphasizes the importance for managers to prioritize factors enhancing employee satisfaction,as it positively correlates with job performance.

Reconsidering Co-Morbid Traits in Explanatory Models of High Dental Anxiety Using a Comparison of Psychiatric and Normal Patient Samples

Explanatory models of co-morbid traits related to dental anxiety (DA) as described in the literature were tested and relative strengths analyzed in two groups of Danish adults, one with psychiatric diagnoses (n = 108) and the other healthy incoming patients at a large dental school teaching clinic (n = 151). Dental Anxiety Scale (DAS) and self-report measures representing three co-morbidity explanatory models, 1) presence of other fears;2) anxiety sensitivity and 3) feelings of vulnerability specific to dental treatment, were collected in subscales of a 53-item questionnaire. Other items identified gender, age, education, income, avoidance behavior and dental symptoms. Frequency, chi-square, odds ratio and logistic regression analyses were performed. Results: All individuals with high DA (DAS > 13) regardless of group, demonstrated significant differences in avoidance of treatment (>2 yr.) versus lower or no anxiety. Patients with psychiatric diagnoses were three times more likely to have high DA and nearly two times more likely to have avoided dental treatment >2 yr.;25.9% reported extreme DA, compared to 9.3% of controls. Models of high general fear levels, predisposing anxiety sensitivity and vulnerability all demonstrated significant and strong association with intensity of dental anxiety in bivariate analyses. Feelings of vulnerability were the strongest predictor of DAS high anxiety, according to logistic regression analyses. Conclusion: Co-morbidity explanatory models as represented in present trait measures appear not to be competitive, but rather explain different aspects of a vulnerability model in high dental anxiety. Higher incidence of DA and treatment avoidance in psychiatric patients requires special attention.

The New Foundation of Organizational Psychology.Trait Activation Theory in the Workplace:Literature Review

Trait Activation Theory(TAT)is a comprehensive examination of the personality-job fit and is based on the model of job performance.This theory’s main argument is how individuals express their personal traits when exposed to trait-relevant situational cues.The trait-relevant situation can be assessed through the cues that play a role in the manifestation of trait-relevant behaviors.The situational cues may originate from social,task,and organization.These cues may provoke or trigger the behaviors related to traits but not related to performance measures.The three central principles suggested in TAT are:(1)personal traits are expressed in the behaviors related to work as responses to the situation cues that are trait-relevant,(2)trait-relevant situation cues originate from social,task,and organization,(3)job performance and work behaviors that are trait expressive are distinct,with job performance to be discussed as valued work behavior.The research conducted and presented below includes articles that are in the majority of the last two decades and the findings suggest that TAT was reviewed usually against managerial roles and qualities.In some articles,TAT was also reviewed and researched together with other major personality theories to explain behavior.