Persona: Martínez Huertas, José Ángel
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Martínez Huertas
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José Ángel
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Publicación Quantum projections on conceptual subspaces: A deeper dive into methodological challenges and opportunities(SAGE, 2024) Martínez Mingo, Alejandro; Olmos, Ricardo; Jorge Botana, Guillermo; Martínez Huertas, José ÁngelIn alignment with the distributional hypothesis of language, the work “Quantum Projections on Conceptual Subspaces” (Martínez-Mingo A, Jorge-Botana G, Martinez-Huertas JÁ, et al. Quantum projections on conceptual subspaces. Cogn Syst Res 2023; 82: 101154) proposed a methodology for generating conceptual subspaces from textual information based on previous work (Martinez-Mingo A, Jorge-Botana G and Olmos R. Quantum approach for similarity evaluation in LSA vector space models. 2020). These subspaces enable the utilization of the quantum model of similarity put forth by Pothos and Busemeyer (Pothos E, Busemeyer J. A quantum probability explanation for violations of symmetry in similarity judgments. In Proceedings of the annual meeting of the cognitive science society, 2011, Vol. 33, No. 33), allowing for the empirical examination of the violations of assumptions concerning symmetry and triangular inequality (Tversky A. Features of similarity. Psychol Rev 1977; 84: 327–352; Yearsley JM, Barque-Duran A, Scerrati E, et al. The triangle inequality constraint in similarity judgments. Prog Biophys Mol Biol 2017; 130: 26–32), as well as the diagnosticity effect (Tversky A. Features of similarity. Psychol Rev 1977; 84: 327–352; Yearsley JM, Pothos EM, Barque-Duran A, et al. Context effects in similarity judgments. J Exp Psychol Gen 2022; 151: 711–717), within a data-driven environment. These psychological biases, deeply studied by authors such as Tversky and Kahneman, inform us about the limitations of modeling psychological similarity measures using tools from classical geometry. This commentary aims to offer methodological clarifications, discuss theoretical and practical implications, and speculate on future directions in this field of research. Concretely, it aims to propose the use of different contours (conceptual or contextual) to generate the subspaces, which lead to subspaces of terms or contexts. Once these contours are defined, a differentiation is proposed between Aggregated Terms Subspaces (ATSs), Aggregated Contexts Subspaces (ACSs), and Aggregated Features Subspaces (AFSs) depending on whether we define the subspaces by grouping the terms or contexts within the contour, or from the latent dimensions of the semantic space obtained in the contour window. Finally, new data is provided on the violation of the triangular inequality assumption through the application of the quantum similarity model to ATSs.Publicación Are valence and arousal related to the development of amodal representations of words? A computational study(['Taylor and Francis Group', 'Routledge'], 2023-11-21) Jorge Botana, Guillermo de; Martínez Mingo, Alejandro; Iglesias, Diego; Olmos, Ricardo; Martínez Huertas, José ÁngelIn this study, we analyzed the relationship between the amodal (semantic) development of words and two popular emotional norms (emotional valence and arousal) in English and Spanish languages. To do so, we combined the strengths of semantics from vector space models (vector length, semantic diversity, and word maturity measures), and feature-based models of emotions. First, we generated a common vector space representing the meaning of words at different developmental stages (five and four developmental stages for English and Spanish, respectively) using the Word Maturity methodology to align different vector spaces. Second, we analyzed the amodal development of words through mixed-effects models with crossed random effects for words and variables using a continuous time metric. Third, the emotional norms were included as covariates in the statistical models. We evaluated more than 23,000 words, whose emotional norms were available for more than 10,000 words, in each language separately. Results showed a curve of amodal development with an increasing linear effect and a small quadratic deceleration. A relevant influence on the amodal development of words was found only for emotional valence (not for arousal), suggesting that positive words have an earlier amodal development and a less pronounced semantic change across early lifespan.Publicación Emotional Valence Precedes Semantic Maturation of Words: A Longitudinal Computational Study of Early Verbal Emotional Anchoring(Wiley, 2021-07-19) Jorge Botana, Guillermo de; Olmos, Ricardo; Martínez Huertas, José ÁngelWe present a longitudinal computational study on the connection between emotional and amodal word representations from a developmental perspective. In this study, children's and adult word representations were generated using the latent semantic analysis (LSA) vector space model and Word Maturity methodology. Some children's word representations were used to set a mapping function between amodal and emotional word representations with a neural network model using ratings from 9-year-old children. The neural network was trained and validated in the child semantic space. Then, the resulting neural network was tested with adult word representations using ratings from an adult data set. Samples of 1210 and 5315 words were used in the child and the adult semantic spaces, respectively. Results suggested that the emotional valence of words can be predicted from amodal vector representations even at the child stage, and accurate emotional propagation was found in the adult word vector representations. In this way, different propagative processes were observed in the adult semantic space. These findings highlight a potential mechanism for early verbal emotional anchoring. Moreover, different multiple linear regression and mixed-effect models revealed moderation effects for the performance of the longitudinal computational model. First, words with early maturation and subsequent semantic definition promoted emotional propagation. Second, an interaction effect between age of acquisition and abstractness was found to explain model performance. The theoretical and methodological implications are discussed.Publicación A Failed Cross-Validation Study on the Relationship between LIWC Linguistic Indicators and Personality: Exemplifying the Lack of Generalizability of Exploratory Studies(MDPI, 2022-10-13) Moreno, José David; Olmos, Ricardo; Martínez Mingo, Alejandro; Jorge Botana, Guillermo de; Martínez Huertas, José Ángel(1) Background: Previous meta-analytic research found small to moderate relationships between the Big Five personality traits and different linguistic computational indicators. However, previous studies included multiple linguistic indicators to predict personality from an exploratory framework. The aim of this study was to conduct a cross-validation study analyzing the relationships between language indicators and personality traits to test the generalizability of previous results; (2) Methods: 643 Spanish undergraduate students were tasked to write a self-description in 500 words (which was evaluated with the LIWC) and to answer a standardized Big Five questionnaire. Two different analytical approaches using multiple linear regression were followed: first, using the complete data and, second, by conducting different cross-validation studies; (3) Results: The results showed medium effect sizes in the first analytical approach. On the contrary, it was found that language and personality relationships were not generalizable in the cross-validation studies; (4) Conclusions: We concluded that moderate effect sizes could be obtained when the language and personality relationships were analyzed in single samples, but it was not possible to generalize the model estimates to other samples. Thus, previous exploratory results found on this line of research appear to be incompatible with a nomothetic approach.Publicación Redundancy, Isomorphism and Propagative Mechanisms between Emotional and Amodal Representations of Words: A Computational Study(['Springer', 'Psychonomic Society'], 2020-08-20) Jorge Botana, Guillermo de; Olmos, Ricardo; Martínez Huertas, José Ángel; Luzón Encabo, José MaríaSome proposals claim that language acts as a link to propagate emotional and other modal information. Thus, there is an eminently amodal path of emotional propagation in the mental lexicon. Following these proposals, we present a computational model that emulates a linking mechanism (mapping function) between emotional and amodal representations of words using vector space models, emotional feature-based models, and neural networks. We analyzed three central concepts within the embodiment debate (redundancy, isomorphism, and propagative mechanisms) comparing two alternative hypotheses: semantic neighborhood hypothesis vs. specific dimensionality hypothesis. Univariate and multivariate neural networks were trained for dimensional (N=11,357) and discrete emotions (N=2,266), and later we analyzed its predictions in a test set (N=4,167 and N=875, respectively). We showed how this computational model could propagate emotional responses to words without a direct emotional experience via amodal propagation, but no direct relations were found between emotional rates and amodal distances. Thereby, we found that there were clear redundancy and propagative mechanisms, but no isomorphism should be assumed. Results suggested that it was necessary to establish complex links to go beyond amodal distances of vector spaces. In this way, although the emotional rates of semantic neighborhoods could predict the emotional rates of target words, the mapping function of specific amodal features seemed to simulate emotional responses better. Thus, both hypotheses would not be mutually exclusive. We also showed that discrete emotions could have simpler relations between modal and amodal representations than dimensional emotions. All these results and their theoretical implications are discussed.Publicación Automated summary evaluation with inbuilt rubric method: An alternative to constructed responses and multiple-choice tests assessments(Taylor and Francis Group, 2019-02-09) Jastrzebska, Olga; Olmos, Ricardo; León, José A.; Martínez Huertas, José ÁngelAutomated Summary Evaluation is proposed as an alternative to rubrics and multiple-choice tests in knowledge assessment. Inbuilt rubric is a recent Latent Semantic Analysis (LSA) method that implements rubrics in an artificially-generated semantic space. It was compared with classical LSA’s cosine-based methods assessing knowledge in a within-subjects design regarding two validation sources: a comparison with the results of rubric scores and multiple-choice tests, and the sensitivity of predicting the academic level of the test-taker. Results showed a higher reliability for inbuilt rubric (from Pearson correlation coefficient .81 to .49) over the classical LSA method (from .61 to .34) and a higher sensitivity using binary logistic regressions and effect sizes to predict academic level. It is concluded that inbuilt rubric has a qualitatively higher reliability and validity than classical LSA methods in a way that is complementary to models based on semantic networks. Thus, it is concluded that new Automated Summary Evaluation approaches such as the inbuilt rubric method can be practical in terms of reliability and efficiency, and, thus, they can offer an affordable and valuable form of knowledge assessment in different educational levels.Publicación Distilling vector space model scores for the assessment of constructed responses with bifactor Inbuilt Rubric method and latent variables(['Springer', 'Psychonomic Society'], 2022-01-11) Olmos, Ricardo; Jorge Botana, Guillermo de; León, José A.; Martínez Huertas, José ÁngelIn this paper, we highlight the importance of distilling the computational assessments of constructed responses to validate the indicators/proxies of constructs/trins using an empirical illustration in automated summary evaluation. We present the validation of the Inbuilt Rubric (IR) method that maps rubrics into vector spaces for concepts’ assessment. Specifically, we improved and validated its scores’ performance using latent variables, a common approach in psychometrics. We also validated a new hierarchical vector space, namely a bifactor IR. 205 Spanish undergraduate students produced 615 summaries of three different texts that were evaluated by human raters and different versions of the IR method using latent semantic analysis (LSA). The computational scores were validated using multiple linear regressions and different latent variable models like CFAs or SEMs. Convergent and discriminant validity was found for the IR scores using human rater scores as validity riteria. While this study was conducted in the Spanish language, the proposed scheme is language-independent and applicable to any language. We highlight four main conclusions: (1) Accurate performance can be observed in topic-detection tasks without hundreds/thousands of pre-scored samples required in supervised models. (2) Convergent/discriminant validity can be improved using measurement models for computational scores as they adjust for measurement errors. (3) Nouns embedded in fragments of instructional text can be an affordable alternative to use the IR method. (4) Hierarchical models, like the bifactor IR, can increase the validity of computational assessments evaluating general and specific knowledge in vector space models. R code is provided to apply the classic and bifactor IR method.Publicación Analyzing Two Automatic Latent Semantic Analysis (LSA) Assessment Methods (Inbuilt Rubric vs. Golden Summary) in Summaries Extracted from Expository Texts(Colegio Oficial de Psicólogos de Madrid, 2018) Jastrzebska, Olga; Mencu, Adrián; Moraleda, Jessica; Olmos, Ricardo; Antonio León, José Antonio; Martínez Huertas, José ÁngelEl objetivo de este estudio es comparar dos métodos de evaluación automática del análisis semántico latente (LSA): Un nuevo método LSA ( Inbuilt Rubric) y un método LSA tradicional ( Golden Summary). Se analizaron dos condiciones del método Inbuilt Rubric: el número de descriptores léxicos que se utilizan para generar la rúbrica (pocos vs. muchos) y una corrección que penaliza el contenido irrelevante incluido en los resúmenes de los estudiantes (corregido vs. no corregido). Ciento sesenta y seis estudiantes divididos en dos muestras (81 estudiantes universitarios y 85 estudiantes de instituto) participaron en este estudio. Los estudiantes resumieron dos textos expositivos que tenían distinta complejidad (difícil/fácil) y longitud (1,300/500 palabras). Los resultados mostraron que el método Inbuilt Rubric imita las evaluaciones humanas mejor que Golden Summary en todos los casos. La similitud con las evaluaciones humanas fue más alta con Inbuilt Rubric ( r = .78 and r = .79) que con Golden Summary ( r = .67 and r = .47) en ambos textos. Además, la versión de Inbuilt Rubric con menor número de descriptores y con corrección es la que obtuvo mejores resultados.Publicación Metacomprehension skills depend on the type of text: An analysis from Differential Item Functioning(Colegio Oficial de Psicólogos del Principado de Asturias, 2019) Antonio León, José Antonio; Olmos, Ricardo; Moreno, José David; Martínez Huertas, José Ángel; Escudero Domínguez, InmaculadaLas habilidades metacomprensivas dependen del tipo de texto: un análisis desde el Funcionamiento Diferencial de los Ítems. Antecedentes: la metacomprensión supone la habilidad que uno mismo posee para juzgar su grado de aprendizaje y comprensión de un texto, adquiriendo una gran importancia en la comprensión lectora. Dado que los procesos de comprensión se encuentran influenciados por las características de los textos, el objetivo de este estudio fue analizar si diferentes tipos de texto afectan de manera significativa a la habilidad metacomprensiva de estudiantes de distintos niveles de Educación Primaria. Método: un total de 823 estudiantes de 4º y 6º de Primaria (9 y 11 años) leyeron tres textos diferentes (narrativo, expositivo y discontinuo) tomados de la prueba estandarizada de comprensión lectora ECOMPLEC.Pri (León, Escudero, y Olmos, 2012). Los estudiantes fueron clasificados por su nivel de metacomprensión obtenido en la prueba. Un Análisis Diferencial del Ítem (DIF) se aplicó para analizar si los procesos de comprensión lectora y de metacomprensión difieren entre tipos de texto y niveles académicos de los participantes. Resultados: los resultados mostraron una notable divergencia en el rendimiento metacognitivo del texto narrativo frente a los textos expositivo y discontinuo. Estas diferencias estaban relacionadas con el nivel académico. Conclusión: el tipo de texto puede tener un gran impacto en las habilidades de metacomprensión y, consecuentemente, en el aprendizaje de textosPublicación Modeling personality language use with small semantic vector subspaces(Elsevier, 2024-12-14) Jorge Botana, Guillermo de; Martínez Mingo, Alejandro; Olmos, Ricardo; Martínez Huertas, José Ángel; Moreno Salinas, David