Tracing Personality Structure in Narratives: A Computational Bottom–Up Approach to Unpack Writers, Characters, and Personality in Historical Context

2020 ◽  
Vol 34 (5) ◽  
pp. 917-943
Author(s):  
Ronald Fischer ◽  
Johannes Alfons Karl ◽  
Markus Luczak–Roesch ◽  
Velichko H. Fetvadjiev ◽  
Adam Grener
Keyword(s):  
Charles Dickens ◽  
Personality Assessment ◽  
Jane Austen ◽  
Historical Context ◽  
Reference Points ◽  
Personality Structure ◽  
Bottom Up ◽  
Personality Psychology ◽  
Historical Texts ◽  
Big Five Model

We present a new method for personality assessment at a distance to uncover personality structure in historical texts. We focus on how two 19th century authors understood and described human personality; we apply a new bottom–up computational approach to extract personality dimensions used by Jane Austen and Charles Dickens to describe fictional characters in 21 novels. We matched personality descriptions using three person–description dictionaries marker scales as reference points for interpretation. Factor structures did not show strong convergence with the contemporary Big Five model. Jane Austen described characters in terms of social and emotional richness with greater nuances but using a less extensive vocabulary. Charles Dickens, in contrast, used a rich and diverse personality vocabulary, but those descriptions centred around more restricted dimensions of power and dominance. Although we could identify conceptually similar factors across the two authors, analyses of the overlapping vocabulary between the two authors suggested only moderate convergence. We discuss the utility and potential of automated text analysis and the lexical hypothesis to (i) provide insights into implicit personality models in historical texts and (ii) bridge the divide between idiographic and nomothetic perspectives. © 2020 European Association of Personality Psychology

Comparing predictive validity in a community sample: High–dimensionality and traditional domain–and–facet structures of personality variation

2020 ◽  
Vol 34 (6) ◽  
pp. 1120-1137
Author(s):  
Gerard Saucier ◽  
Kathryn Iurino ◽  
Amber Gayle Thalmayer
Keyword(s):  
Personality Assessment ◽  
Community Sample ◽  
High Dimensionality ◽  
Structure Model ◽  
Predictive Capacity ◽  
Personality Psychology ◽  
Measurement Models ◽  
Efficient Route ◽  
Personality Models ◽  
Criterion Variables

Prediction of outcomes is an important way of distinguishing, among personality models, the best from the rest. Prominent previous models have tended to emphasize multiple internally consistent “facet” scales subordinate to a few broad domains. But such an organization of measurement may not be optimal for prediction. Here, we compare the predictive capacity and efficiency of assessments across two types of personality–structure model: conventional structures of facets as found in multiple platforms, and new high–dimensionality structures emphasizing those based on natural–language adjectives, in particular lexicon–based structures of 20, 23, and 28 dimensions. Predictions targeted 12 criterion variables related to health and psychopathology, in a sizeable American community sample. Results tended to favor personality–assessment platforms with (at least) a dozen or two well–selected variables having minimal intercorrelations, without sculpting of these to make them function as indicators of a few broad domains. Unsurprisingly, shorter scales, especially when derived from factor analyses of the personality lexicon, were shown to take a more efficient route to given levels of predictive capacity. Popular 20th–century personality–assessment models set out influential but suboptimal templates, including one that first identifies domains and then facets, which compromise the efficiency of measurement models, at least from a comparative–prediction standpoint. © 2020 European Association of Personality Psychology

scholarly journals Jean Talairach: a cerebral cartographer

2019 ◽  
Vol 47 (3) ◽  
pp. E12 ◽  
Author(s):  
Maya Harary ◽  
G. Rees Cosgrove
Keyword(s):  
Historical Context ◽  
Reference Points ◽  
Career Trajectory ◽  
Functional Neurosurgery ◽  
Tumor Biopsy ◽  
Stereotaxic Atlas ◽  
Selective Approach ◽  
Assessment And Treatment ◽  
Cerebral Localization ◽  
Anterior Capsulotomy

Although French psychiatrist-turned-neurosurgeon Jean Talairach (1911–2007) is perhaps best known for the stereotaxic atlas he produced with Pierre Tournoux and Gábor Szikla, he has left his mark on most aspects of modern stereotactic and functional neurosurgery. In the field of psychosurgery, he expressed critique of the practice of prefrontal lobotomy and subsequently was the first to describe the more selective approach using stereotactic bilateral anterior capsulotomy. Turning his attention to stereotaxy, Talairach spearheaded the team at Hôpital Sainte-Anne in the construction of novel stereotaxic apparatus. Cadaveric investigation using these tools and methods resulted in the first human stereotaxic atlas where the use of the anterior and posterior commissures as intracranial reference points was established. This work revolutionized the approach to cerebral localization as well as leading to the development of numerous novel stereotactic interventions by the Sainte-Anne team, including tumor biopsy, interstitial irradiation, thermal ablation, and endonasal procedures. Together with epileptologist Jean Bancaud, Talairach invented the field of stereo-electroencephalography and developed a robust scientific methodology for the assessment and treatment of epilepsy. In this article the authors review Talairach’s career trajectory in its historical context and in view of its impact on modern stereotactic and functional neurosurgery.

scholarly journals The relationship between cognitive processing of affective verbal material and the basic personality structure

Psihologija ◽  
2010 ◽  
Vol 43 (3) ◽  
pp. 329-353 ◽  
Author(s):  
Ana Orlic
Keyword(s):  
Cognitive Processing ◽  
Verbal Material ◽  
Affective Priming ◽  
Personality Structure ◽  
Decision Task ◽  
Affective Valence ◽  
Facilitation Effect ◽  
Big Five Model ◽  
The Subject ◽  
The Relationship

The aim of this study was to investigate the relationship between cognitive processing of affective verbal material and the basic personality structure. For the purposes of research a new experiment was created, where affective priming was measured in a lexical decision task. The term affective priming stands for facilitation in recognition of the stimuli that comes after the presentation of stimuli of the same valence. In this experiment, two words were presented on a screen in front of the subject (stimuli-prime and stimuli-target). Those two words were of the same or different affective valence, and the subject's were instructed to respond whether the second word on the screen had a meaning or not. The basic personality structure was defined by the 'Big five' model and the Disintegration model and measured by NEO PI-R and Delta 10 questionnaires. The results of the affective priming experiment indicated a strong effect of positive facilitation and much weaker effect off negative facilitation. Two significant functions were extracted by quasicanonical correlation analysis. The first function showed correlation between the effect of positive facilitation and all of the subscales of Neuroticism, Extraversion and Conscientiousness (NEO PI-R), as well as all sub dimensions of Disintegration (DELTA 10). The second one indicated to a correlation between the negative facilitation effect and some subscales of Neuroticism, Extraversion and Agreeableness (NEO PI-R), as well as all subscales of Disintegration (DELTA 10).

Episode 3: Personality Structure and Change (Transcript)

2021 ◽  
Author(s):  
Emorie D Beck
Keyword(s):  
European Association ◽  
Historical Perspective ◽  
Personality Structure ◽  
Personality Psychology

This is a show on the science of how people are different from one another, where these differences come from, how they develop, and why they matter. The podcast's hosts are Lisanne de Moor, René Mõttus, and Rebekka Weidmann, three personality researchers. It is a collaboration of the European Journal of Personality and the European Association of Personality Psychology (EAPP), and sponsored by EAPP. www.personalitypsychologypodcast.com. In this episode, we hear a presentation by Emorie Beck on her research on nomothetic and idiographic approaches to personality structure and change, couched in a historical perspective.

Objections to the HEXACO Model of Personality Structure—and why those Objections Fail

2020 ◽  
Vol 34 (4) ◽  
pp. 492-510 ◽  
Author(s):  
Michael C. Ashton ◽  
Kibeom Lee
Keyword(s):  
Social Media ◽  
European Association ◽  
Personality Structure ◽  
Personality Psychology ◽  
Personality Research ◽  
Target Article ◽  
Social Media Platforms ◽  
Dimensional Models ◽  
Hexaco Model

The six–dimensional HEXACO model of personality structure and its associated inventory have increasingly been used in personality research. But in spite of the evidence supporting this structure and demonstrating its advantages over five–dimensional models, some researchers continue to use and promote the latter. Although there has been little overt, organized argument against the adoption of the HEXACO model, we do hear sporadic offerings of reasons for retaining the five–dimensional systems, usually in informal conversations, in manuscript reviews, on social media platforms, and occasionally in published works. In this target article, we list all of the objections to the HEXACO model that we have heard of, and we then explain why each objection fails. © 2020 European Association of Personality Psychology

Social-Cognitive Theory of Personality Assessment

2001 ◽  
Vol 5 (1) ◽  
pp. 33-51 ◽  
Author(s):  
Daniel Cervone ◽  
William G. Shadel ◽  
Simon Jencius
Keyword(s):  
Social Cognitive Theory ◽  
Personality Assessment ◽  
Social Cognitive ◽  
Cognitive Theory ◽  
Scientific Explanation ◽  
Personality Structure ◽  
Alternative Theory ◽  
Cognitive Principles ◽  
The Individual ◽  
Determinants Of Action

This article presents a social-cognitive theory of personality assessment. We articulate the implications of social-cognitive theories of personality for the question of what constitutes an assessment of personality structure and behavioral dispositions. The theory consists of 5 social-cognitive principles of assessment. Personality assessments should (a) distinguish the task of assessing internal personality structures and dynamics from that of assessing overt behavioral tendencies, (b) attend to personality systems that function as personal determinants of action, (c) treat measures of separate psychological and physiological systems as conceptually distinct, (d) employ assessments that are sensitive to the unique qualities of the individual, and (e) assess persons in context. These principles are illustrated through a review of recent research. Social-cognitive theory is distinguished from an alternative theory of personality structure and assessment, 5-factor theory, by articulating the strategies of scientific explanation, conceptions of personality structure and dispositions, and the assessment practices that differentiate the approaches.

scholarly journals Do We Understand Life after Genocide? Center and Periphery in the Construction of Knowledge in Postgenocide Rwanda

2010 ◽  
Vol 53 (1) ◽  
pp. 41-59 ◽  
Author(s):  
Bert Ingelaere
Keyword(s):  
Knowledge Construction ◽  
Historical Context ◽  
Ordinary People ◽  
Culturally Specific ◽  
Bottom Up ◽  
Construction Of Knowledge ◽  
The Social

Abstract:Do we really understand life after genocide? A reflection on the construction of knowledge in and on Rwanda reveals that it is rife with contradictory assertions and images, and that there is a discrepancy between image and reality. This article attempts to map the center(s) of knowledge construction in postgenocide Rwanda, the place not only where policy is made, but also where knowledge is actively construed, managed, and controlled. It argues that an overall cultivation of the aesthetics of progress and a culturally specific communication code have contributed to an active interference in the scientific construction of knowledge. It stresses the need for scholars and observers to reveal the social and historical context for the knowledge being generated. It also urges them to physically and mentally move away from the center of society: to adopt a bottom-up perspective that captures the voices of ordinary people.

scholarly journals Bottom Up Construction of a Personality Taxonomy

2020 ◽  
Vol 36 (6) ◽  
pp. 923-934 ◽  
Author(s):  
David M. Condon ◽  
Dustin Wood ◽  
René Mõttus ◽  
Tom Booth ◽  
Giulio Costantini ◽  
...  
Keyword(s):  
Personality Assessment ◽  
Survey Methodology ◽  
Bottom Up ◽  
Trait Variance ◽  
Item Level ◽  
Item Characteristics ◽  
Programmatic Evaluation ◽  
Quantitative Properties ◽  
Comprehensive Framework ◽  
Different Levels

Abstract. In pursuit of a more systematic and comprehensive framework for personality assessment, we introduce procedures for assessing personality traits at the lowest level: nuances. We argue that constructing a personality taxonomy from the bottom up addresses some of the limitations of extant top-down assessment frameworks (e.g., the Big Five), including the opportunity to resolve confusion about the breadth and scope of traits at different levels of the organization, evaluate unique and reliable trait variance at the item level, and clarify jingle/jangle issues in personality assessment. With a focus on applications in survey methodology and transparent documentation, our procedures contain six steps: (1) identification of a highly inclusive pool of candidate items, (2) programmatic evaluation and documentation of item characteristics, (3) test-retest analyses of items with adequate qualitative and quantitative properties, (4) analysis of cross-ratings from multiple raters for items with adequate retest reliability, (5) aggregation of ratings across diverse samples to evaluate generalizability across populations, (6) evaluations of predictive utility in various contexts. We hope these recommendations are the first step in a collaborative effort to identify a comprehensive pool of personality nuances at the lowest level, enabling subsequent construction of a robust hierarchy – from the bottom up.

scholarly journals Personality Research and Assessment in the Era of Machine Learning

2020 ◽  
Vol 34 (5) ◽  
pp. 613-631 ◽  
Author(s):  
Clemens Stachl ◽  
Florian Pargent ◽  
Sven Hilbert ◽  
Gabriella M. Harari ◽  
Ramona Schoedel ◽  
...  
Keyword(s):  
Machine Learning ◽  
Personality Assessment ◽  
Latent Variables ◽  
Learning Models ◽  
Personality Psychology ◽  
Fine Grained ◽  
Personality Research ◽  
Key Issues ◽  
Complex Relationships ◽  
Machine Learning Models

The increasing availability of high–dimensional, fine–grained data about human behaviour, gathered from mobile sensing studies and in the form of digital footprints, is poised to drastically alter the way personality psychologists perform research and undertake personality assessment. These new kinds and quantities of data raise important questions about how to analyse the data and interpret the results appropriately. Machine learning models are well suited to these kinds of data, allowing researchers to model highly complex relationships and to evaluate the generalizability and robustness of their results using resampling methods. The correct usage of machine learning models requires specialized methodological training that considers issues specific to this type of modelling. Here, we first provide a brief overview of past studies using machine learning in personality psychology. Second, we illustrate the main challenges that researchers face when building, interpreting, and validating machine learning models. Third, we discuss the evaluation of personality scales, derived using machine learning methods. Fourth, we highlight some key issues that arise from the use of latent variables in the modelling process. We conclude with an outlook on the future role of machine learning models in personality research and assessment.

Psychometric and Validity Issues in Machine Learning Approaches to Personality Assessment: A Focus on Social Media Text Mining

2020 ◽  
Vol 34 (5) ◽  
pp. 826-844 ◽  
Author(s):  
Louis Tay ◽  
Sang Eun Woo ◽  
Louis Hickman ◽  
Rachel M. Saef
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
Text Mining ◽  
Personality Assessment ◽  
Ground Truth ◽  
Psychometric Validation ◽  
Learning Approaches ◽  
Text Data ◽  
Personality Psychology ◽  
Social Media Text

In the age of big data, substantial research is now moving toward using digital footprints like social media text data to assess personality. Nevertheless, there are concerns and questions regarding the psychometric and validity evidence of such approaches. We seek to address this issue by focusing on social media text data and (i) conducting a review of psychometric validation efforts in social media text mining (SMTM) for personality assessment and discussing additional work that needs to be done; (ii) considering additional validity issues from the standpoint of reference (i.e. ‘ground truth’) and causality (i.e. how personality determines variations in scores derived from SMTM); and (iii) discussing the unique issues of generalizability when validating SMTM for personality assessment across different social media platforms and populations. In doing so, we explicate the key validity and validation issues that need to be considered as a field to advance SMTM for personality assessment, and, more generally, machine learning personality assessment methods. © 2020 European Association of Personality Psychology

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