Assessing the Big Five personality traits using real-life static facial images
There is ample evidence that morphological and social cues in a human face provide signals of human personality and behaviour. Previous studies have discovered associations between the features of artificial composite facial images and attributions of personality traits by human experts. We present new findings demonstrating the statistically significant prediction of a wider set of personality features (all the Big Five personality traits) for both men and women using real-life static facial images. Volunteer participants (N = 12,447) provided their face photographs (31,367 images) and completed a self-report measure of the Big Five traits. We trained a cascade of artificial neural networks (ANNs) on a large labelled dataset to predict self-reported Big Five scores. The highest correlations between observed and predicted personality scores were found for conscientiousness (0.360 for men and 0.335 for women) and the mean effect size was 0.243, exceeding the results obtained in prior studies using ‘selfies’. The findings strongly support the possibility of predicting multidimensional personality profiles from static facial images using ANNs trained on large labelled datasets. Future research could investigate the relative contribution of morphological features of the face and other characteristics of facial images to predicting personality.
One of the most challenging data analysis tasks of modern High Energy Physics experiments is the identification of particles. In this proceedings we review the new approaches used for particle identification at the LHCb experiment. Machine-Learning based techniques are used to identify the species of charged and neutral particles using several observables obtained by the LHCb sub-detectors. We show the performances of various solutions based on Neural Network and Boosted Decision Tree models.
This book constitutes the refereed proceedings of the 11th International Conference on Intelligent Data Processing, IDP 2016, held in Barcelona, Spain, in October 2016.
The 11 revised full papers were carefully reviewed and selected from 52 submissions. The papers of this volume are organized in topical sections on machine learning theory with applications; intelligent data processing in life and social sciences; morphological and technological approaches to image analysis.
We present a series of studies aimed at the development and the validation of a new Russian-language instrument measuring existential fulfilment based on the hierarchical structure of the 4 existential fundamental motivations developed by A. Längle. Based on phenomenological descriptions and focus groups, we created a 94-item set. The structural validation study used 2 online samples (N = 818 and N = 215). Using hierarchical cluster analysis, expert-rating procedure, and confirmatory factor analysis with cross-validation we arrived at a hierarchically structured set of 36 items grouped into 4 scales (forming a general index of existential fulfilment) and 12 subscales corresponding to theoretical prerequisites of fundamental motivations. The scales demonstrated acceptable reliability (α in the .79-.88 range, .93 for the general score). In 3 samples (N = 658, N = 215, N = 105) we sought evidence of convergent and discriminant validity of TEM against measures of well-being (emotional, social, and psychological well-being, subjective happiness, satisfaction with life), basic psychological need satisfaction, self-esteem, psychopathology (anxiety, depression, alienation), and the Big Five traits using correlation and regression analyses. Two other studies explored the associations of existential fulfilment with other demographic and psychological variables (gender, age, self-control, reflexive processes) in a large sample (N = 3766) and investigated TEM scores in individuals with binge eating disorder (N = 193). The findings show the convergent validity of existential fulfilment indicators against well-being measures based on different theoretical approaches, as well as discriminant and criterion validity of existential fundamental motivation scales. We also discuss the psychometric challenges associated with existential concepts and propose approaches to their solution.
This book constitutes the proceedings of the 8th International Conference on Analysis of Images, Social Networks and Texts, AIST 2019, held in Kazan, Russia, in July 2019.
The 24 full papers and 10 short papers were carefully reviewed and selected from 134 submissions (of which 21 papers were rejected without being reviewed). The papers are organized in topical sections on general topics of data analysis; natural language processing; social network analysis; analysis of images and video; optimization problems on graphs and network structures; analysis of dynamic behaviour through event data.
Background: There are a limited number of aphasia language tests in the majority of the world’s commonly spoken languages. Furthermore, few aphasia tests in languages other than English have been standardised and normed, and few have supportive psychometric data pertaining to reliability and validity. The lack of standardised assessment tools across many of the world’s languages poses serious challenges to clinical practice and research in aphasia. Aims: The current review addresses this lack of assessment tools by providing conceptual and statistical guidance for the development of aphasia assessment tools and establishment of their psychometric properties. Main Contribution: A list of aphasia tests in the 20 most widely spoken languages is included. The pitfalls of translating an existing test into a new language versus creating a new test are outlined. Factors to be considered in determining test content are discussed. Further, a description of test items corresponding to different language functions is provided, with special emphasis on implementing important controls in test design. Next, a broad review of principal psychometric properties relevant to aphasia tests is presented, with specific statistical guidance for establishing psychometric properties of standardised assessment tools. Conclusions: This article may be used to help guide future work on developing, standardising and validating aphasia language tests. The considerations discussed are also applicable to the development of standardised tests of other cognitive functions.
Results of empirical studies of alienation are described, based on cultural-historical and activity approach to meaning and to the existential-analytical model of dialogue with the world. Two versions of the (Russian) Subjective Alienation Questionnaire based on the Alienation test by Maddi et al. were validated on student and Internet samples (N = 901). In this test alienation showed negative correlations with meaning, hardiness, self-determination and other subjective and psychological well-being variables. Significant age- and profession-related differences in alienation were found and discussed. Future research directions of social and psychological aspects of alienation and existential analysis effects on alienation are proposed.
Meta-analytic research in psychology of academic performance proved that Big Five Conscientiousness and Openness to Experience predict scholastic achievements of university students (O’Connor, Paunonen, 2007; Poropat, 2009). But we claim that psychological predictiors of academic success depend on educational environment and can be culture-related. We examined 176 2nd and 3rd year economy and computer science university students in Russia with the Big Five – Ipsative version test (Shmelyov, 2010) and discovered that GPA and USE (United State Examination in Russia) scores are significantly correlated with Agreeableness (r = 0.15; p < 0.01 for GPA and r = 0.22 p < 0.01 for USE math) and Neuroticism (r = 0.2, p < 0.01 for GPA and r = -0,17; p < 0,01 for USE math). We suppose that the difference between our result and results provided by the meta-analyses mentioned above can be explained by the differences in educational environment in Russia and other countries. We assume that big number of classes and relatively small amount of individual and analytical assignments create the environment where Agreeableness and Neuroticism are important for the academic success.
The distractive effects on attentional task performance in different paradigms are analyzed in this paper. I demonstrate how distractors may negatively affect (interference effect), positively (redundancy effect) or neutrally (null effect). Distractor effects described in literature are classified in accordance with their hypothetical source. The general rule of the theory is also introduced. It contains the formal prediction of the particular distractor effect, based on entropy and redundancy measures from the mathematical theory of communication (Shannon, 1948). Single- vs dual-process frameworks are considered for hypothetical mechanisms which underpin the distractor effects. Distractor profiles (DPs) are also introduced for the formalization and simple visualization of experimental data concerning the distractor effects. Typical shapes of DPs and their interpretations are discussed with examples from three frequently cited experiments. Finally, the paper introduces hierarchical hypothesis that states the level-fashion modulating interrelations between distractor effects of different classes.
This article describes the expierence of studying factors influencing the social well-being of educational migrants as mesured by means of a psychological well-being scale (A. Perrudet-Badoux, G.A. Mendelsohn, J.Chiche, 1988) previously adapted for Russian by M.V. Sokolova. A statistical analysis of the scale's reliability is performed. Trends in dynamics of subjective well-being are indentified on the basis the correlations analysis between the condbtbions of adaptation and its success rate, and potential mechanisms for developing subjective well-being among student migrants living in student hostels are described. Particular attention is paid to commuting as a factor of adaptation.