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Copyright of Retos: Nuevas Perspectivas de Educación Física, Deporte y Recreación is the property of Federacion Espanola de Asociaciones de Docentes de Educacion Fisica and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This narrative review examines the relationship between dopamine-related genetic polymorphisms, personality traits, and athletic success. Advances in sports genetics have identified specific single nucleotide polymorphisms (SNPs) in dopamine-related genes linked to personality traits crucial for athletic performance, such as motivation, cognitive function, and emotional resilience. This review clarifies how genetic variations can influence athletic predisposition through dopaminergic pathways and environmental interactions. Key findings reveal associations between specific SNPs and enhanced performance in various sports. For example, polymorphisms such as COMT Val158Met rs4680 and BDNF Val66Met rs6265 are associated with traits that could benefit performance, such as increased focus, stress resilience and conscientiousness, especially in martial arts. DRD3 rs167771 is associated with higher agreeableness, benefiting teamwork in sports like football. This synthesis underscores the multidimensional role of genetics in shaping athletic ability and advocates for integrating genetic profiling into personalized training to optimize performance and well-being. However, research gaps remain, including the need for standardized training protocols and exploring gene–environment interactions in diverse populations. Future studies should focus on how genetic and epigenetic factors can inform tailored interventions to enhance both physical and psychological aspects of athletic performance. By bridging genetics, personality psychology, and exercise science, this review paves the way for innovative training and performance optimization strategies. [ABSTRACT FROM AUTHOR]

This paper intends to explore entrepreneurship intention among the youth by examining their personality traits. The respondents of this study were accounting students in their final year from seven public universities across Malaysia. A validated questionnaire was employed and distributed to representatives of each university, obtaining a total of 756 responses. The collected data was analyzed using descriptive statistics and utilized partial least square-structural equation modelling (PLS-SEM) to analyze the hypotheses. The results revealed that personality traits influence entrepreneurship intention of accounting students' and conscientiousness being the most significant trait with a coefficient of 0.612. This paper suggests that personality traits namely conscientiousness, extraversion, openness to experience and agreeableness can boost entrepreneurship attitude, thus it should be optimized systematically into the education context to shape young personalities that are inclined towards entrepreneurship. Essentially, Ministry of Higher Institution, universities, colleges, and schools are advised to shape entrepreneurial personalities through the education curriculum and frequent practical sessions with inspiring entrepreneurs in the industry. Further, integrating the elements of personality traits into entrepreneurship education can serve as a guide for financial management of a business. [ABSTRACT FROM AUTHOR]

Recent studies have revived the issue of whether the five-factor personality model or Big Five is the most valid to summarize the most relevant personality traits or whether, on the contrary, the basic structure of personality traits would better fit a six-factor model such as the HEXACO model: Honesty–Humility (H), Emotionality (E), Extraversion (X), Agreeableness (A), Conscientiousness (C), and Openness to Experience (O). In a Spanish community sample of 682 adults, the factorial structure of the 30 facets of the NEO-Revised Personality Inventory (NEO PI-R) and its 16 facets common to the HEXACO model was analyzed. In two subsamples of participants, the internal structure of the NEO PI-R, of 30 and 16 facets, fit the five-factor Big Five model better than the six-factor HEXACO model. In addition, the internal 30-facet structure of the NEO-PI-R replicated that obtained in the original US validation and those previously obtained in Spain, although the latter used different participant samples (people evaluated in personnel selection processes, university students). These results suggest that, at least in Spain, the five-factor personality model or Big Five is still the most valid taxonomy of personality traits. [ABSTRACT FROM AUTHOR]

Copyright of Acta Colombiana de Psicologia is the property of Universidad Catolica de Colombia and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Although personality is vital for creative achievement, little is known about the personality profiles of eminent creators from different domains. The role personality plays in being recognized and acclaimed by public opinion is even more overlooked. In our study, we performed linguistic analyses of postaward interviews on a large sample (N = 225) of Nobel Prize laureates (1957–2019) in art (literature) and science (chemistry, economic sciences, medicine, and physics) to infer creators' personalities. We examined (a) between-domain differences in personality and (b) the links between personality and professional (space devoted to laureates in Encyclopedia Britannica) and popular (the number of language versions of Wikipedia profiles) recognition. When compared to scientists, writers were more open, introvert, and neurotic and less conscientious. While personality was not related to the space devoted to laureates in Encyclopedia Britannica, the number of Wikipedia language versions was not only much higher for writers than for scientists but also positively linked with writers' Openness and Extraversion and negatively linked with their Agreeableness. We discuss the results in light of between-domain differences in personality and in light of the mechanisms of creative people gaining recognition. [ABSTRACT FROM AUTHOR]

The links between personality and religious orientation have been studied in various religions and populations across the globe. However, an important limitation is that the relationship was not researched in LGBTQI populations. With this study, we aimed to fill this gap. 128 LGBTQI individuals responded to two questionnaires measuring the Big Five personality factors and the bi-dimensional model of Intrinsic and Extrinsic Religious Orientation. Our results show that men reported higher levels of Religious Orientation than women and non-binary participants. Neuroticism and Conscientiousness were significantly related to Intrinsic religious orientation, but only the former was a significant predictor of it. The results are discussed in terms of theoretical and practical implications. [ABSTRACT FROM AUTHOR]

This study seeks to examine what traits, "myths" and skills pupils will attribute to good geography teachers, and whether their assessments are influenced by gender, age, grade and satisfaction with a teacher. The sample consists of 150 high school pupils in Serbia. The survey consisted of four parts: socio-demographic characteristics, Big Five Inventory, good teacher myths, and good geography teacher skills. The results showed that pupils believe that good geography teachers have to be impartial, friendly and conscientious in the first place. Also, 13 high school teachers were also interviewed. The data are somewhat in line with previous research, but also indicate pupils' specific expectations of their geography teachers and teachers' awareness that they are not just ordinary teachers.

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 of language facets and complex features such as hierarchical relationships or long-term dependencies. This makes them suitable to classify multilabel 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 theMyPersonality 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, andweighted averages. The results reveal ERNIE is the topperforming 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 testedmodels 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. [ABSTRACT FROM AUTHOR]

This empirical study aimed to analyse the influence of the personality traits of owner-managers in small and medium-sized enterprises (SMEs) on organisational ambidexterity (OA). Based on the existing literature, five hypotheses were formulated about the relationships between the Big Five personality traits and organisational ambidexterity. A second-order structural equation model was used with a sample of 224 Portuguese SMEs in the sector of information technology (IT), telecommunications, and audio-visual and IT consultancy. The results obtained suggest that the personality traits of extraversion, neuroticism (versus emotional stability) and conscientiousness have a significant influence on organisational ambidexterity. These results are consistent with the research and demonstrate that owner-managers' personality traits influence organisational ambidexterity in SMEs. Theoretical and practical implications are explored. [ABSTRACT FROM AUTHOR]

Academic interest in athletic performance is ongoing. To examine the correlation between athletic performance and athletes' personality types, data extraction in line with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines was completed in October 2021, and a meta-analysis was performed using 180 data from 18 selected papers using the "meta" package version 4.8-4 of R Studio 3.3.3. As a result, these selected studies proved to have reliable quality in proceeding with this study via quality assessment. The overall effect of personality on athletic performance (AP) was ESr = 0.124, p < 0.01. Furthermore, only conscientiousness (ESr = 0.178, p < 0.001) and extroversion (ESr = 0.145, p < 0.01), among the five personality types, showed statistically significant results, and these two personality types had a positive correlation with performance. In the publication bias test, this study found that (a) agreeableness had a publication bias; but, with an additional test using trim-and-fill, (b) the effect was not significant enough to be considered. In addition, the analysis of the moderating effects was conducted in four aspects, and all moderating effect analyses showed statistically significant differences between the groups, demonstrating the heterogeneity of this study. Therefore, this study found a significant relationship between personality and athletic performance and showed the importance of conscientiousness and extroversion. [ABSTRACT FROM AUTHOR]

Research on decision-making often relies on controlled laboratory studies, which are de-tached from real-life scenarios. Analyzing self-reported, long-term decision outcomes from a military real-world contexts can provide a robust foundation for identifying individual factors that differentiate decision-making capabilities among individuals. The role of per-sonality factors and decision-making styles is analyzed in the decision-making process, us-ing the Decision Outcomes Inventory (DOI), developed by Bruine de Bruine et al. in a sam-ple of the population of 178 active militaries, of which 135 men and 39 women. The results of the decision-making process are significantly predicted by the anxious decision-making style, i.e., people who tend to experience negative feelings during decision-making end up having better results when making decisions. The strong link between the anxious decision-making style and emotional stability is highlighted by the structure of the network used in the analysis. Since the opposite pole of emotional stability is neuroticism, we can say that people with an anxious decision-making style face a wide range of feelings specific to this decision-making style, such as fear, and insecurity, so they postpone deciding until they find the best solution. [ABSTRACT FROM AUTHOR]

Personality is a unique trait that allows discriminating between individuals. It can be defined by a set of stable characteristics of an individual that may affect their interactions, relationships, attitudes, behaviors, and even psychological health. Currently, with the advent of social networking sites that provide user-generated text content, personality trait recognition has gained a lot attention. These texts from social networks keep a record of users' psychological activity over time, which makes it a vital piece of information to analyze the users' personality traits. This study proposes a stacked ensemble model combining multiple classic machine learning classifiers using different semantic and lexical features, as well as deep learning algorithms, and distinct word embedding techniques to develop a personality recognition model. The performance of the proposed ensemble model has been assessed using the gold standard MyPersonality dataset. The results demonstrate that the proposed framework outperforms different ensemble model architectures, classical machine learning, and deep learning-based algorithms, as well as state-of-the-art studies, achieving an average accuracy of 72.69%.

Objective: We investigate the applicability of the Big Five model in rural Southeast Asia and thereby challenge recent concerns about the validity of the model in developing countries. Method: We use a novel data set on personality traits from rural Thailand and Vietnam (N = 3811 individuals). In our analysis, we (i) assess the factor structure of the data, (ii) test the internal consistency of the items, (iii) compare the traits across two consecutive survey waves, and (iv) employ regressions to demonstrate the economic relevance of the traits. Results: The results demonstrate a five‐factor structure that fits the Big Five model. We observe changes in personality traits over time but Cohen's d coefficients only range between 0.06 and 0.21. The average rank‐order stability, measured by the test–retest correlation of the Big Five between the two consecutive waves, lies at 0.21. Individual changes in personality traits over time relate to experienced shocks and appear to be largely independent of age, gender, and education. We further find that openness and emotional stability positively correlate with rural incomes. Conclusions: While there is skepticism, pertaining to the use of personality trait models in developing countries, our study demonstrates that their importance and usage cannot be rejected. [ABSTRACT FROM AUTHOR]

Mobile streaming is increasingly viewed as a major advancement in the wireless industry, as it enables users to consume content without any time or space restrictions. Mobile TV serves as an excellent example of streaming, providing services for watching TV content on mobile devices. While previous studies have explored video-on-demand (VOD) purchasing factors in mobile TV, it is rare to find research examining differences based on users’ mobile TV usage types, such as subscribers and free users. Consequently, we investigated VOD purchase factors for 310 subscribers and 311 free mobile TV users. In other words, using 621 survey responses, we analyze the influence of personality traits, intrinsic and extrinsic motivations, and mobile-related factors on users’ VOD purchase intentions and behavior. Our findings indicate that mobile TV utilization, hedonic needs, and subjective norms are positively related to VOD purchases, and that neuroticism, extraversion, openness, and conscientiousness positively impact mobile TV utilization. We also examine the relationships between the constructs within two sub-groups to highlight the differing perceptions and behavioral patterns of these groups regarding mobile TV utilization and VOD purchases. Theoretical and practical implications are discussed as well.

Personality is a stable construction, which is associated with thoughts, emotions and behaviors of human. Any technology involved in understanding, analyzing and predicting human behaviors may benefit from personality recognition. Accurately recognizing the personality will contribute to the research of human-computer interaction, recommendation system, cyberspace security, etc. Social media provides high-quality data for personality recog-nition, while classic personality measurement methods such as self-report scales and projective tests can no longer match the social media data in the age of big data. Moreover, the current mainstream personality recognition methods based on machine learning still have lots of room for performance improvement. Therefore, this paper investigates the literature on personality recognition based on social media data, introduces the background knowledge of personality recognition and summarizes the research status according to the data types of recognition model input used, specifically based on social text data, social image data, social application data and multimodal data. Finally, this paper proposes seven future research directions of personality recognition based on social media data.

The primary aim of the paper is to conduct research on the personality traits and pre-competition anxiety of Esports and sports players, in addition to confirming differences in personality and pre-competition anxiety between the two examined groups. The research has been conducted on 67 (N=67) subjects, 30 of whom are semi-professional or professional gamers who participate in state-level and regional-level competitions. The remaining 37 subjects are the highest-ranked athletes in Bosnia and Herzegovina. The t-test, a type of inferential statistic, has been used to determine statistical differences in disposition between the arithmetic means of the two groups, using BFI-44 (α=0.78) and CSAI-2 (α=0.60) measuring instruments. It has been anticipated that the Esports players are ranked lower at Extraversion (E) and Agreeableness (A) levels, while their Neuroticism (N) level is higher compared to the results of the athletes. The research indicates that all of the three hypotheses regarding the Big Five Model have been confirmed – on the scale of Extraversion (E) with significance levels of p=0.000 (p

The primary aim of the paper is to conduct research on the personality traits in esport players and athletes, in addition to confirming differences in personality between the two examined groups. The research has been conducted on 67 (N=67) examinees, 30 of whom are semi-professional or professional esports players who participate in state-level and regional-level competitions. The remaining 37 examinees are the highest-ranked athletes in Bosnia and Herzegovina. T-test, a type of inferential statistic, has been used to determine statistical differences in disposition between the arithmetic means of the two groups, using the BFI-44 (a=0.78) measuring instrument. It has been anticipated that esports players would be ranked lower on Extraversion (E), Agreeableness (A), and Conscientiousness (C), but higher on the Neuroticism (N) and Openness (O) dimensions compared to athletes. The research indicates that four of the five hypotheses have been confirmed - on the scale of Extraversion (E) with significance levels of p=.000 (p

Purpose: Behavioral finance proposes that psychology of the individual plays a vital role in investment decisions. Therefore, this study aims to examine the influence of one of the important disciplines of psychology, i.e. personality on investment decision-making by incorporating financial satisfaction as an intervening variable and gender as a moderator. Design/methodology/approach: The data of 406 valid responses were collected through structured questionnaires from individual investors of Indian stock market and analyzed using structural equation modeling. Several invariance tests were also conducted to perform the multigroup analysis of gender on the mediated model. Findings: The results revealed that extraversion, agreeableness, conscientiousness and neuroticism significantly influence investment decision-making through financial satisfaction. While financial satisfaction significantly mediates the indirect relationships between personality traits and investment decision-making for both males and females, no significant differences among males and females were found in the mediated model. Research limitations/implications: The current study covers a limited geographical area of North India. In addition to this, it is cross-sectional in nature and incorporates only limited factors for predicting investment decisions. Practical implications: The study possesses numerous significant implications for financial practitioners, advisors, investors, academicians and researchers in the field of behavioral finance. Originality/value: This study suggests a moderated mediation approach, which incorporates financial satisfaction as a mediator and gender as a moderator. To the best of the authors' knowledge, so far, no study has been conducted in this context, and it will enhance the understanding of investment decisions of individual investors. [ABSTRACT FROM AUTHOR]

Mobile streaming is increasingly viewed as a major advancement in the wireless industry, as it enables users to consume content without any time or space restrictions. Mobile TV serves as an excellent example of streaming, providing services for watching TV content on mobile devices. While previous studies have explored video-on-demand (VOD) purchasing factors in mobile TV, it is rare to find research examining differences based on users' mobile TV usage types, such as subscribers and free users. Consequently, we investigated VOD purchase factors for 310 subscribers and 311 free mobile TV users. In other words, using 621 survey responses, we analyze the influence of personality traits, intrinsic and extrinsic motivations, and mobile-related factors on users' VOD purchase intentions and behavior. Our findings indicate that mobile TV utilization, hedonic needs, and subjective norms are positively related to VOD purchases, and that neuroticism, extraversion, openness, and conscientiousness positively impact mobile TV utilization. We also examine the relationships between the constructs within two sub-groups to highlight the differing perceptions and behavioral patterns of these groups regarding mobile TV utilization and VOD purchases. Theoretical and practical implications are discussed as well. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Frontiers of Computer Science & Technology is the property of Beijing Journal of Computer Engineering & Applications Journal Co Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Despite many decades' worth of investigations into associations between music and personality, the empirical findings are quite scant and scattered. Perhaps, this is because musicians are a diverse group of people, with far-reaching musical interests and wide-ranging personalities. Little research, however, has investigated whether musicians' choice of musical genre bears a relationship to their personalities. In this study, we explore the limited literature on the relationship between music ensemble membership and personality by investigating personality differences between jazz and classical ensemble musicians on the Big Five personality dimensions. Musicians (N = 221) were recruited from college music ensembles, an introductory psychology course, a Facebook page, and Amazon Mechanical Turk. Participants completed the Big Five Inventory (BFI), a validated self-report personality questionnaire, and analyses were conducted to compare the scores of jazz musicians to the scores of classical musicians. Significant differences emerged between jazz and classical musicians' personalities, with gender playing a mediating role. These results may be beneficial for music educators and directors, as knowledge that specific personality traits predict music ensemble membership may help guide instruction techniques, communication, understanding between musicians of different musical genres, and general cooperation between music educators/directors and their ensembles. [ABSTRACT FROM AUTHOR]

Copyright of Social Sciences & Humanities Studies / Društvene i Humanističke Studije (DHS) is the property of Faculty of Humanities & Social Sciences, University of Tuzla and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Automated personality trait detection from text data has emerged and gained a great deal of attention in the subject area of affective computing and sentiment analysis. Most previous work has focused on features engineering such as linguistic styles and psycholinguistic databases which have correlations with personality. Recently, natural language processing has been affected significantly with transfer learning based on feature extraction and fine-tuning pre-trained language models. We propose a new deep learning-based model for personality prediction and classification using both data and classifier level fusion. The model gets benefit from, transfer learning in natural language processing through leading pre-trained language models namely Elmo, ULMFiT, and BERT. The proposed model demonstrates the powerfulness of the introduced method to be a promising personality prediction model. When evaluating the proposed method, results show a competitive and significant accuracy enhancement of about 1.25% and 3.12% in comparison to the most recent results for the two gold standard Essays and myPersonality datasets for personality detection.

Introduction Research suggests that certain personality traits influence the frequency of social media use. However, the potential effect of social media use on personality states merits investigation as well, in light of the personality dynamics approach. Material and methods We conducted an experimental study in which 325 Instagram users were asked to count selfies and emoticons on their Instagram profiles (experimental condition) or their phones (control condition). Subsequently, all participants responded to questions from the Big Five personality inventory and scale to measure the need for uniqueness in consumption. Results Instagram users had a higher neuroticism state and a higher need for uniqueness compared with the controls. In terms of the other Big Five states, we observed no differences between the study conditions. Conclusions Our study explores the novel direction of the relationship between social media use and personality, suggesting that using Instagram can temporarily change personality states.

Although parenting is considered a turning point that reduces non‐normative behaviours, some parents choose to occasionally continue using various drugs. The present study examines the personality and demographic characteristics of these parents by comparing three parent groups: those who do not use at all, those who use only cannabis and those who use other substances. Three self‐report quantitative questionnaires: Demographic, Patterns of use of psychoactive substances and the Big Five Personality traits questionnaire, were administered to 627 parents. The findings show that the proportion of unmarried and secular men is higher in the group of parents who use substances. They also were found to be younger and less educated than the other parent's groups. We examined the parents' personality characteristics using the Big Five model and found that parents who use substances occasionally exhibit higher levels of extraversion and openness to experiences, and lower levels of conscience. The differences found in the characteristics of parents who use cannabis to those who use other substances, indicate the normativeness of cannabis use among parents, and reflect the need for intervention programs among parents who use substances, which may have a great influence on drug use among their children. [ABSTRACT FROM AUTHOR]

The BFI-44 and BFI-10 are widely used, open-source measures of the Big Five Model of personality. Exploratory factor analyses and exploratory structural equation modeling produce models with non-negligible cross-loadings, creating unclear factor structures and confounded validity evidence. Further, no studies have independently confirmed the structural validity of the scale using confirmatory factor analyses. In Study 1, with a sample of community members (n = 345), we demonstrated that the BFI-44 and BFI-10 fail to demonstrate acceptable data-model fit and contain an excessive number of correlational residual statistics (i.e., BFI-44: 36%; BFI-10: 42%). In Study 2, with a sample of undergraduate students (n = 110), we created a version of the BFI-10 with strong structural and construct validity, the BFI-10-R. Using an EFA, we selected the top two items from the BFI-44 for each Big Five trait with the strongest loadings onto their factor and with the weakest cross-loadings. We then confirmed the new 10-item factor structure using a confirmatory factor analysis and found a model with strong global and local fit in both samples. This new model had few significant correlational residual statistics, strong convergent and divergent validity, and strong internal consistency. Researchers may consider using the BFI-10-R in place of the BFI-10 due to its preferable psychometric properties. [ABSTRACT FROM AUTHOR]

Human personality is significantly represented by those words which he/she uses in his/her speech or writing. As a consequence of spreading the information infrastructures (specifically the Internet and social media), human communications have reformed notably from face to face communication. Generally, Automatic Personality Prediction (or Perception) (APP) is the automated forecasting of the personality on different types of human generated/exchanged contents (like text, speech, image, video, etc.). The major objective of this study is to enhance the accuracy of APP from the text. To this end, we suggest five new APP methods including term frequency vector-based, ontology-based, enriched ontology-based, latent semantic analysis (LSA)-based, and deep learning-based (BiLSTM) methods. These methods as the base ones, contribute to each other to enhance the APP accuracy through ensemble modeling (stacking) based on a hierarchical attention network (HAN) as the meta-model. The results show that ensemble modeling enhances the accuracy of APP. [ABSTRACT FROM AUTHOR]

One of the major platforms today to express your emotions, expressions, feelings, and views about something or about any product is social media. People put forth what they feel, therefore their individual posts can be judged as a reflection of their personality, but how to judge a personality of a person based on social media posts and that too of say large data, say thousands, and produce analysis on it. In our studies, we specialize in using deep learning to build a classifier that can classify individuals according to their Myers-Briggs Type Index (MBTI) solely using textual content samples from their social media posts as an input. There are two reasons for developing such a classifier. First, due to the fact social media is so ubiquitous, one of these classifiers might have lots of statistics to degree character, permitting extra human beings to realize their MBTI character type, possibly extra reliably and faster. Our second incentive is the opportunity that our classifier can be more correct than the cutting-edge assessments, as evidenced with the aid of using the low retest mistakes price for character assessments executed with the aid of using expert psychologists. It may be possible to use our classification method to verify the accuracy of these first assessments, to give individuals more confidence in their results. In some cases, a text classification may be more comprehensive than a single personality assessment. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to test and discuss the relationships between the Big-Five personality traits (agreeableness, conscientiousness, extraversion, neuroticism, and openness to experience) and social entrepreneurial intention. This study applies the technique of structural equation modeling to explore relationships among latent constructs. Survey responses were collected from 753 undergraduate students to compile the analysis. The results confirm that individuals with different personality traits behave differently in relation to social entrepreneurial intention. While agreeableness, extraversion, and openness to experience have positive effects, neuroticism and conscientiousness negatively impact social entrepreneurial intention. Policymakers should build an environment that fosters agreeableness, extraversion, and openness to experience—these are the primary factors that influence SEI. Educators can design personality development programs to help students perfect the personalities that match becoming social entrepreneurs. Future research should be expanded to incorporate other factors such as culture, background, education, and experience to provide a more general view of the impact of personality on intentions.

The main objective of this work is to examine the prevalence of psychopathy in the general adult population from the main currently existing theoretical perspectives of psychopathy, using for this purpose the five-factor or Big Five model as a common language that allows the comparison and integration of the personality traits considered as defining psychopathy by these different perspectives. The NEO Personality Inventory-Revised (NEO PI-R) was applied to a sample of 682 adults of the general Spanish population. The prevalence of clinical and subclinical psychopathy was calculated according to six different definitions of these two constructs based on Hare’s, Lilienfeld’s, triarchic, and DSM-5-hybrid models, and the simultaneous presence of a minimum number of personality traits that differed from the sample mean by one standard deviation. Prevalence rates for the different definitions were consistently low, indicating that the prevalence of clinical psychopathy in the general Spanish population is around 0.55%, and that of subclinical psychopathy is around 1.65%. There were no significant sex differences in the prevalence of psychopathy. These results question the alarmist claims that warn about the existence in society of a very high number of people with psychopathy who can cause many social, economic, physical, and psychological damage to others.

• Some team members' personality traits weakly relate to team performance. • The standard deviation of neuroticism shows the highest correlation. • The relationships change by context, such as team tenure or performance types. The relationships between team members' personality traits and their team's performance have been studied for decades, yet the relationships remain unclear. The field has evolved as new assessments of team performance and novel insights from empirical studies are introduced. Furthermore, collaboration and team-relevant topics have been spotlighted by policymakers and stakeholders. Thus, new systematic investigations into such relationships are needed. Accordingly, we sought to fill these gaps and produce more integrative results by updating and extending earlier meta -analyses by exploring several moderators. We focused on task performance and the means and standard deviations of team members' Big Five personality traits. The results revealed that several team personality traits were weakly related to team performance and key moderators influenced the relationships. [ABSTRACT FROM AUTHOR]

The popularity of social media has drawn the attention of researchers who have conducted cross-disciplinary studies examining the relationship between personality traits and behavior on social media. Most current work focuses on personality prediction analysis of English texts, but Indonesian has received scant attention. Therefore, this research aims to predict user’s personalities based on Indonesian text from social media using machine learning techniques. This paper evaluates several machine learning techniques, including naive Bayes (NB), K-nearest neighbors (KNN), and support vector machine (SVM), based on semantic features including emotion, sentiment, and publicly available Twitter profile. We predict the personality based on the Big Five personality model, the most appropriate model for predicting user personality in social media. We examine the relationships between the semantic features and the Big Five personality dimensions. The experimental results indicate that the Big Five personality exhibit distinct emotional, sentimental, and social characteristics and that SVM outperformed NB and KNN for Indonesian. In addition, we observe several terms in Indonesian that specifically refer to each personality type, each of which has distinct emotional, sentimental, and social features. [ABSTRACT FROM AUTHOR]

We aimed to analyze personality-related determinants of physical activity among Polish and Spanish physical education (PE) students. The study was conducted among 219 Polish and 280 Spanish PE students, using the International Physical Activity Questionnaire (IPAQ) and the NEO-FFI Personality Inventory. Compared with Spanish PE students, their Polish counterparts are characterized by a higher level of extraversion and conscientiousness and a lower level of neuroticism. The level of total physical activity for all students was 8,697.21 METs, and this value was higher among Polish students. Among Polish and Spanish PE students, the level of total, vigorous, and moderate physical activity increased along with the increase in extraversion, while a decrease occurred along with the increase in neuroticism. The level of each domain of physical activity also increased in line with the intensification of student conscientiousness. In moderation analyses, it was shown that the home country of students may be considered a moderator of the relationship between conscientiousness and total exercise in such a way that the physical activity increased along with the increase in conscientiousness only among the Polish students. In addition, the country is a moderator of the correlation between moderate physical activity and neuroticism (p = 0.031), openness (p = 0.049), and conscientiousness (p = 0.019), with moderate activity only decreasing among Polish students and increasing along with the increase in openness and conscientiousness. Positive correlations among physical activity, extraversion, and conscientiousness, as well as negative ones with neuroticism, were demonstrated among Polish and Spanish students, and also the moderating impact of the country on the correlation between personality-related dimensions and physical activity.