Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
57
datasets available to search
ShareScore release 0.9.0
Dataset results
57 results for “Emotional intelligence”
BRAIN Journal-Brain-Like Artificial Intelligence for Automation-Figure 16. Architecture for Affective Situation Assessment of Perceptual Images (Internal Connections between Emotions are not Depicted for Better Clarity of the Graphic)
<p>Based on the concept of affective neuro-symbols, a model was developed according to<br> which emotions can be represented by affective neuro-symbolic networks (see right half of Figure<br> 16, referred to as architecture of “internal perception” in contrast to the “external perception”<br> architecture of the left half of Figure 16, which has already been presented in Section 4.2).<br> The individual affective neuro-symbols (depicted as circles) represent different emotions<br> (fear, anger, guilt, joy, rage, panic, love, happiness, etc.).</p>
BRAIN Journal-Brain-Like Artificial Intelligence for Automation-Figure 15. Input Sources of an Affective Neuro-Symbol Representing an Emotion
<p>Based on the descriptions given above and the concept of neuro-symbolic information<br> processing outlined in Section 4.2, so-called “affective neuro-symbols” were defined for the<br> affective situation assessment architecture (see Figure 15). These affective neuro-symbols can<br> principally receive information from four different sources: (1) body states, (2) objects and events<br> perceived in the environment (external perception), (3) from other emotions and (4) cognitive<br> (reasoning) processes. An input from one of these sources can in certain circumstances already be<br> sufficient to activate an affective neuro-symbol. Different sources can either have an exhibitory or<br> inhibitory effect on the activation of an affective neuro-symbol.</p>
BRAIN Journal-Cursor Movement – a Valuable Indicator in Intelligent System Design-Figure 5. Emotional flow after 3 hours of graphical editing
<p>To resume, we started with a product interface, found a way to determine two opposite states, than used that way to map user interaction with the product and determine the emotional answer to that interface. The results can then be used to improve product design, to elicit certain emotional responses, etc. For example, in this case, due to the rapid movement (anger) patterns in the aligning phase, a layout that minimizes this can be developed, using a shortcut menu or dynamically appearing guidelines. Furthermore, the user interface can be imagined to be able to learn working patterns and shift the shortcut menu from an aligning menu, if it detects anger patterns, into a color/shape picking menu, if it detects relaxation patterns, therefore assessing the emotional impact and improving the design of the interface in the same time.</p>
Emotional Quotient Inventory - Young Version / Inventario de Inteligencia Emocional - Versión para Niños // EMOTIONAL INTELLIGENCE-EQi-YV_Data_IC_T6-Post
<p>Answers given by students in the sixth grade of Primary Education to the 60 items of The Emotional Quotient Inventory: Youth Version (EQ-i: YV) by Bar-On and Parker (2000; Spanish validation by Ferrándiz, Hernández, Bermejo, Ferrando, and Sáinz, 2012). Data collected in public schools in Castellón (Spain) in the spring of the school year 2015-16. The calculation of the 5 Socioemotional Dimensions is included: Intrapersonal, Interpersonal, Stress Management, Adaptability, and General Mood. To learn more about our research and access to other datasets of this or other measures, follow the link <a href="https://www.uji.es/departaments/psi/base/opengrei/">GREI Longitudinal Project</a>.</p> <p> </p> <p>Respuestas que los alumnos/as de sexto curso de Educación Primaria dan a los 60 ítems del Inventario de Inteligencia Emocional: Versión para Niños (EQ-i:YV) de Bar-On and Parker (2000; validado para población española por Ferrándiz, Hernández, Bermejo, Ferrando, y Sáinz, 2012). Datos recogidos en centros públicos de Castellón (España) en primavera del curso escolar 2015-16. Se incluye el cálculo de las 5 Dimensiones Socioemocionales: Intrapersonal, Interpersonal, Manejo del Estrés, Adaptabilidad y Estado de Ánimo General. Para saber más sobre nuestra investigación y acceder a otros ficheros de datos de esta medida o de otras, siga el enlace <a href="https://www.uji.es/departaments/psi/base/opengrei/">Proyecto Longitudinal GREI</a>.</p>
Emotional Quotient Inventory - Young Version / Inventario de Inteligencia Emocional – Versión para Niños // EMOTIONAL INTELLIGENCE-EQi-YV_Data_IC_T3-Post
<p>Answers given by students in the third grade of Primary Education to the 60 items of The Emotional Quotient Inventory: Youth Version (EQ-i: YV) by Bar-On and Parker (2000; Spanish validation by Ferrándiz, Hernández, Bermejo, Ferrando, and Sáinz, 2012). Data collected in public schools in Castellón (Spain) in the spring of the school year 2012-13. The calculation of the 5 Socioemotional Dimensions is included: Intrapersonal, Interpersonal, Stress Management, Adaptability, and General Mood. To learn more about our research and access to other datasets of this or other measures, follow the link <a href="https://www.uji.es/departaments/psi/base/opengrei/">GREI Longitudinal Project</a>.</p> <p> </p> <p>Respuestas que los alumnos/as de tercer curso de Educación Primaria dan a los 60 ítems del Inventario de Inteligencia Emocional (EQ-i:YV) de Bar-On and Parker (2000; validado para población española por Ferrándiz, Hernández, Bermejo, Ferrando, y Sáinz, 2012). Datos recogidos en centros públicos de Castellón (España) en primavera del curso escolar 2012-13. Se incluye el cálculo de las 5 Dimensiones Socioemocionales: Intrapersonal, Interpersonal, Manejo del Estrés, Adaptabilidad y Estado de Ánimo General Para saber más sobre nuestra investigación y acceder a otros ficheros de datos de esta medida o de otras, siga el enlace <a href="https://www.uji.es/departaments/psi/base/opengrei/">Proyecto Longitudinal GREI</a>.</p>
Emotional Quotient Inventory - Young Version / Inventario de Inteligencia Emocional – Versión para Niños // EMOTIONAL INTELLIGENCE-EQi-YV_Data_CC-CS_T6-Post
<p>Answers given by students in the sixth grade of Primary Education to the 60 items of The Emotional Quotient Inventory: Youth Version (EQ-i: YV) by Bar-On and Parker (2000; Spanish validation by Ferrándiz, Hernández, Bermejo, Ferrando, and Sáinz, 2012). Data collected in public schools in Castellón and Seville (Spain) in the spring of the school year 2014-15. The calculation of the 5 Socioemotional Dimensions is included: Intrapersonal, Interpersonal, Stress Management, Adaptability, and General Mood. To learn more about our research and access to other datasets of this or other measures, follow the link <a href="https://www.uji.es/departaments/psi/base/opengrei/">GREI Longitudinal Project</a>.</p> <p> </p> <p>Respuestas que los alumnos/as de sexto curso de Educación Primaria dan a los 60 ítems del Inventario de Inteligencia Emocional (EQ-i:YV) de Bar-On and Parker (2000; validado para población española por Ferrándiz, Hernández, Bermejo, Ferrando, y Sáinz, 2012). Datos recogidos en centros públicos de Castellón y Sevilla (España) en primavera del curso escolar 2014-15. Se incluye el cálculo de las 5 Dimensiones Socioemocionales: Intrapersonal, Interpersonal, Manejo del Estrés, Adaptabilidad y Estado de Ánimo General Para saber más sobre nuestra investigación y acceder a otros ficheros de datos de esta medida o de otras, siga el enlace <a href="https://www.uji.es/departaments/psi/base/opengrei/">Proyecto Longitudinal GREI</a></p>
Emotional Quotient Inventory - Young Version / Inventario de Inteligencia Emocional - Versión para Niños // EMOTIONAL INTELLIGENCE-EQi-YV_Data_IC_T5-Post
<p>Answers given by students in the fifth grade of Primary Education to the 60 items of The Emotional Quotient Inventory: Youth Version (EQ-i: YV) by Bar-On and Parker (2000; Spanish validation by Ferrándiz, Hernández, Bermejo, Ferrando, and Sáinz, 2012). Data collected in public schools in Castellón (Spain) in the spring of the school year 2014-15. The calculation of the 5 Socioemotional Dimensions is included: Intrapersonal, Interpersonal, Stress Management, Adaptability, and General Mood. To learn more about our research and access to other datasets of this or other measures, follow the link <a href="https://www.uji.es/departaments/psi/base/opengrei/">GREI Longitudinal Project</a>.</p> <p> </p> <p>Respuestas que los alumnos/as de quinto curso de Educación Primaria dan a los 60 ítems del Inventario de Inteligencia Emocional: Versión para Niños (EQ-i:YV) de Bar-On and Parker (2000; validado para población española por Ferrándiz, Hernández, Bermejo, Ferrando, y Sáinz, 2012). Datos recogidos en centros públicos de Castellón (España) en primavera del curso escolar 2014-15. Se incluye el cálculo de las 5 Dimensiones Socioemocionales: Intrapersonal, Interpersonal, Manejo del Estrés, Adaptabilidad y Estado de Ánimo General. Para saber más sobre nuestra investigación y acceder a otros ficheros de datos de esta medida o de otras, siga el enlace <a href="https://www.uji.es/departaments/psi/base/opengrei/">Proyecto Longitudinal GREI</a>.</p>
Use of artificial intelligence techniques for the recognition of human emotions: a bibliometric analysis
<p>Human emotion recognition with AI uses physiological, audiovisual, and linguistic signals. Despite its importance and great progress in emotion recognition, several challenges remain in generalization and evaluation through standards and shared data, as well as other research gaps. Therefore, the objective is to analyze the scientific production on the use of artificial intelligence techniques for the recognition of human emotions. This study uses bibliometric analysis following the guidelines of the PRISMA-2020 statement for literature reviews. Based on the results of the bibliometrics on the use of artificial intelligence techniques in for the recognition of human emotions, significant conclusions are obtained that improve the understanding of the current panorama in this field of research. A growing interest in the subject is observed during the years 2023, 2022, 2021 and 2020, which demonstrates the relevance and potential of artificial intelligence in the recognition of human emotions. A cubic polynomial growth in the number of scientific articles is observed, demonstrating a constant expansion of knowledge and support for future trends. Leading authors and journals are identified, highlighting global collaboration in China and India. The thematic evolution shows maturity and progressive specialization, with emerging concepts that promise future research and innovative applications.</p>
Dataset of Emotional intelligence and mood in the beauty contest game
<p>This site provides access to the dataset in the article "Emotional Intelligence and Mood in the Beauty Contest Game: An Experimental Study." The study explores emotional intelligence and mood's impact on strategic decision-making within the Beauty Contest Game framework. Results offer compelling evidence of their influence on strategic guessing and reasoning depth. The dataset includes responses from 96 participants, assessing emotional intelligence, mood categories, and strategic decision details. This resource is crucial for understanding and validating study findings, shedding light on decision-making dynamics and implications for psychology, economics, and organizational behavior. The dataset's availability encourages further research on emotions in decision-making, serving as a foundation for exploring the interrelationship between emotional intelligence, mood, and strategic behavior.</p>
Data Files for the study "Exploring risk-taking behaviour as a function of cognitive flexibility and emotional intelligence"
<p><span>Risk-taking behaviour refers to how one decides to act with the possibility of negative outcomes which is often pursued in the hope of achieving a lucrative reward, and it can happen in various circumstances, which makes it important to study and understand the key factors behind this cognitive process. The present study focused on understanding these dynamics with emotional intelligence and cognitive flexibility. The present study incorporated a healthy sample (<em>n=</em>121) whose emotional intelligence was assessed with MSREIS-R, risk-taking with GDT and cognitive flexibility with WCST. The findings suggested that cognitive flexibility and sub-scale of emotional intelligence did impact risk-taking behaviour, while no moderating effect was found between them. However, the sub-scales of emotional intelligence did predict cognitive flexibility hinting at their interactive relationship which does not erase the possibility of them not affecting risk-taking behaviour completely.<span> </span></span></p> <p>Emotional intelligence questionnaire and manuals, an Excel file consisting of Emotional Intelligence Score, SPSS file, Software file (Inquisit Program file), the link to the task script and other important links, Game of dice task(raw and summary data), Wisconsin Card Sorting Test (raw and summary data).</p>
Emotional intelligence and school climate data from Spain, Norway, and Poland in 2019
<p>Dataset of the published open access article: Luque González, R., Romera, E., Gómez-Ortiz, O., Wiza, A., Laudańska-Krzemińska, I., Antypas, K., & Muller, S. (2022). Emotional intelligence and school climate in primary school children in Spain, Norway, and Poland. <em>Psychology, Society & Education</em>, <em>14</em>(3), 29–37. https://doi.org/10.21071/psye.v14i3.15122</p>
Effectiveness of Online Emotional Intelligence Training
ClinicalTrials.gov study NCT06751745. IPD Sharing: NO. Countries: 1. Publications: 6.
Emotional Intelligence Skills Health Leaders Need During Covid-19
ClinicalTrials.gov study NCT04694014. IPD Sharing: YES. Countries: 1. Publications: 5.
Study of a PST-Trained Voice-Enabled Artificial Intelligence Counselor (SPEAC) for Adults With Emotional Distress (Phase 1)
ClinicalTrials.gov study NCT04524104. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Mediating effects of Trait Emotional Intelligence on the association between Adverse Childhood Experiences (ACEs) and Self-reported Health
<p>Data for two studies which investigate the role of trait emotional intelligence in resilience following adverse childhood experiences. </p>
Relationship between academic stress, emotional intelligence and eating behavior in university students
<p>Emotional intelligence refers to the group of capabilities that enable people to regulate mood and feelings, especially the perception of stress. Although the reasons are not fully understood, there is a link between stress, eating behavior, and emotional intelligence. Our objective was to relate emotional intelligence, academic stress, and eating behavior among Psychology and Biology students at the University of Panama. We determined the association between academic stress, clarity, attention, and emotional repair scores, as well as eating habits at the beginning and end of the semester.</p> <p>Compared to psychology students, biology students feel more academic stress. Psychology students have greater emotional clarity and attentiveness. There is no association between perceived stress, emotional intelligence, and eating behavior. We recommend incorporating physiological variables and instruments that assess the concept of emotional eating.</p> <p>This file includes the coding of the variables, as well as the scores obtained by each participant.</p>
Emotional Intelligence and Authentic Leadership. A comparative study of university students in Chile, Spain, and Mexico.
<pre><span>Research database titled: </span><strong><span>Emotional Intelligence and Authentic Leadership. A comparative study of university students in Chile, Spain, and Mexico.</span></strong></pre> <pre></pre>
Study of a PST-Trained Voice-Enabled Artificial Intelligence Counselor(SPEAC) for Adults With Emotional Distress (Phase 2)
ClinicalTrials.gov study NCT05603923. IPD Sharing: Not stated. Countries: 1. Publications: 2.
Childhood Traumas, and Personality Beliefs and Emotional Intelligence
ClinicalTrials.gov study NCT05847335. IPD Sharing: YES. Countries: 1. Publications: 13.
The Feasibility of Motivational Interviewing on Emotional Intelligence, Dispositional Optimism, and Adherence to Care Practices Among Patients With Permanent Pacemaker
ClinicalTrials.gov study NCT05883514. IPD Sharing: NO. Countries: 1. Publications: 1.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.