La técnica del Ánalisis de la Semántica Latente (LSA/LSI) como modelo informático de la comprensión del texto y el discurso: una aproximación distribuida al análisis semántico

Programa de doctorado de calidad: comprensión del texto y del discursoTesis doctoral inédita leída en la Universidad Autónoma de Madrid, Facultad de Psicología. Departamento de Psicología Social y de Metodología. Fecha de lectura: 10 de diciembre de 2010El formato de esta tesis consiste en una colección de cuatro manuscritos individuales, que han sido recientemente aceptados o enviados para publicación a revistas internacionales de psicología experimental, lingüística o tecnología

Predicting Word Maturity from Frequency and Semantic Diversity: A Computational Study

Semantic word representation changes over different ages of childhood until it reaches its adult form. One method to formally model this change is the word maturity paradigm. This method uses a text sample for each age, including adult age, and transforms the samples into a semantic space by means of Latent Semantic Analysis. The representation of a word at every age is then compared with its adult representation via computational maturity indices. The present study used this paradigm to explore to the impact of word frequency and semantic diversity on maturation indices. To do this, word maturity indices were extracted from a Spanish incremental corpus and validated, using correlation scores with Age of Acquisition and Word Difficulty indices from previous studies. The results show that both frequency and semantic diversity predict word maturity but that the predictive capacity of frequency decreases as exposure to language increases. The latter result is discussed in terms of inductive processes suggested in previous studies

Can personality traits be measured analyzing written language? a meta-analytic study on computational methods

In the last two decades, empirical evidence has shown that personality traits could be related to the characteristics of written language. This study describes a meta-analysis that synthesizes 23 independent estimates of the correlations between the Big Five major personality traits, and some computationally obtained indicators from written language. The results show significant combined estimates of the correlations, albeit small to moderate according to Cohen's conventions to interpret effect sizes, for the five traits (between r = 0.26 for agreeableness and neuroticism, and 0.30 for openness). These estimates are moderated by the type of information in the texts, the use of prediction mechanisms, and the source of publication of the primary studies. Generally, the same effective moderators operate for the five traits. It is concluded that written language analyzed through computational methods could be used to extract relevant information of personality. But further research is still needed to consider it as predictive or explanatory tool for individual difference

Quantifying the ideational context: political frames, meaning trajectories and punctuated equilibria in Spanish mainstream press during the Catalan nationalist challenge

This article presents a quantitative method for mapping semantic spaces and tracing political frames’ trajectories, that facilitate the analysis of the connections between changes in ideas and socio-political phenomena. We test our approach in Spain, where the Catalan conflict fostered a competition in terms of decontestation of meanings of key political concepts. Using unsupervised machine learning, we track the salience, level of semantic fragmentation and fluctuations in meanings of 216 frames in the two largest Spanish newspapers, El País and El Mundo, throughout 8 years. This is achieved via the extraction, vectorization, and comparison of over 70,000 words. We apply Latent Semantic Analysis, an innovative methodology for the alignment of semantic spaces, and new institutional theory. Our exploratory study suggests that the evolution of many nationalism-related frames resembles a punctuated equilibrium model, and that political events in Catalonia, acted as critical junctures, altering the meanings reflected in the Spanish press

Exploring the Assessment of Summaries: Using Latent Semantic Analysis to Grade Summaries Written by Spanish Students

In this study we propose an integrated method to automatically assess summaries using LSA. The method is based on a regression equation calculated with a corpus of a hundred summaries (the training sample), and is validated on a different sample of summaries (the validation sample). The equation incorporates two parameters extracted from LSA: semantic similarity and vector length. A total of 396 students drawn from four stages of education participated in the study. The summaries of a short narrative text written by each participant were evaluated on a scale of 0-10 by four human graders and the scores compared to the evaluation of the summaries using LSA. The results supported that incorporating both parameters into the method resulted more successful than the traditional cosine measure, and that LSA showed a similar level of sensitivity to the quality of the summaries produced in different academic stages as that shown by the human graders. (C) 2013 The Authors. Published by Elsevier Ltd.This work was supported by Grant SEJ2006-09916 from the Spanish Ministry of Science and Technology and PSI 2009-31932 by the Spanish Ministry of Education.León, JA.; Olmos, R.; Escudero Domínguez, I.; Jorge-Botana, G.; Perry, DR. (2013). Exploring the Assessment of Summaries: Using Latent Semantic Analysis to Grade Summaries Written by Spanish Students. Elsevier. 83:151-155. https://doi.org/10.1016/j.sbspro.2013.06.0291511558

Collaborative Versus Individual Learning Experiences in Virtual Education: The Effects of a Time Variable

In this study we analyzed a time effect variable on the performance of collaborative versus individual tasks. Thirty- one postgraduate students carried out two online collaborative learning tasks and two online individual tasks as part of a university course. The results of an ANOVA did not show significant effects of time or task type variables, although the effect of interaction was significant. At the beginning of the course (T1) the students 'performance was significantly higher in the collaborative tasks, while at the end of the course (T2) this trend was reversed, with the students' performance in individual tasks being significantly higher than in the collaborative tasks. The results suggest implications for when to incorporate collaborative learning tasks in virtual learning environments. (C) 2013 The Authors. Published by Elsevier Ltd.This research was partly supported by a faculty research grant from the National Distance Learning University (Universidad Nacional de Educación a Distancia, UNED, Spain, 2011V/PUNED/0005) and the Spanish Ministry of Science and Technology (PSI2009-13932).Escudero Domínguez, I.; León, JA.; Perry, DR.; Olmos, R.; Jorge-Botana, G. (2013). Collaborative Versus Individual Learning Experiences in Virtual Education: The Effects of a Time Variable. Elsevier. 83:367-370. https://doi.org/10.1016/j.sbspro.2013.06.072S3673708

Impact of the first wave of the SARS-CoV-2 pandemic on the outcome of neurosurgical patients: A nationwide study in Spain

Objective To assess the effect of the first wave of the SARS-CoV-2 pandemic on the outcome of neurosurgical patients in Spain. Settings The initial flood of COVID-19 patients overwhelmed an unprepared healthcare system. Different measures were taken to deal with this overburden. The effect of these measures on neurosurgical patients, as well as the effect of COVID-19 itself, has not been thoroughly studied. Participants This was a multicentre, nationwide, observational retrospective study of patients who underwent any neurosurgical operation from March to July 2020. Interventions An exploratory factorial analysis was performed to select the most relevant variables of the sample. Primary and secondary outcome measures Univariate and multivariate analyses were performed to identify independent predictors of mortality and postoperative SARS-CoV-2 infection. Results Sixteen hospitals registered 1677 operated patients. The overall mortality was 6.4%, and 2.9% (44 patients) suffered a perioperative SARS-CoV-2 infection. Of those infections, 24 were diagnosed postoperatively. Age (OR 1.05), perioperative SARS-CoV-2 infection (OR 4.7), community COVID-19 incidence (cases/10 5 people/week) (OR 1.006), postoperative neurological worsening (OR 5.9), postoperative need for airway support (OR 5.38), ASA grade =3 (OR 2.5) and preoperative GCS 3-8 (OR 2.82) were independently associated with mortality. For SARS-CoV-2 postoperative infection, screening swab test <72 hours preoperatively (OR 0.76), community COVID-19 incidence (cases/10 5 people/week) (OR 1.011), preoperative cognitive impairment (OR 2.784), postoperative sepsis (OR 3.807) and an absence of postoperative complications (OR 0.188) were independently associated. Conclusions Perioperative SARS-CoV-2 infection in neurosurgical patients was associated with an increase in mortality by almost fivefold. Community COVID-19 incidence (cases/10 5 people/week) was a statistically independent predictor of mortality. Trial registration number CEIM 20/217

Expert systems

Todos intuimos lo que significa razonamiento deductivo en base a nuestra experiencia. Quien más, quien menos ha aplicado una regla general a un conjunto de hechos. Muchos hemos tenido una planta aquejada de alguna enfermedad y hemos chequeado algunos asertos para comprobar el posible problema e incluso la posible solución. Puntitos blancos, deformación en los tallos, hojas retorcidas, entonces la planta tiene "araña blanca”. Un sistema experto basado en reglas es un tipo de sistema que hace un tratamiento de los hechos con reglas formalizadas de manera lógica. Cuando se dice de manera lógica se está aludiendo a que están expresadas en lógica deductiva. Como lógica deductiva cuenta a priori con un conjunto de reglas y hechos con los que el sistema hará inferencias, es decir, generará otros hechos o consecuencias. En este texto se hace una leve introducción a los sistemas expertos.Depto. de Psicobiología y Metodología en Ciencias del ComportamientoFac. de Psicologíaunpu

Random Forest

Anteriormente hemos visto los árboles de decisión (en caso contrario, acudir al texto base sobre árboles de decisión). Se explicaba entonces que dicha técnica trataba de encontrar una secuencia de particiones en las variables independientes que fuese reduciendo el ruido en la variable dependiente. El ruido era la entropía. Pues bien, puede decirse que los Bosques Aleatorios son una expansión de lo ya visto con los Árboles de Decisión, pero esta vez tomando de la muestra total de datos diferentes submuestras de menor tamaño (muestras con reemplazo). Esto se hace en aras a conseguir una mejor generalización del modelo. Haciendo diversos árboles sobre esas submuestras conseguimos mayor estabilidad y generalización del modelo. En este breve texto se explican los aspectos importantes de la técnica.Depto. de Psicobiología y Metodología en Ciencias del ComportamientoFac. de Psicologíaunpu

K-means

Una de las técnicas más empleadas para la exploración de los datos es la técnica de K-medias. Todos hemos visto alguna vez en forma de gráficos su producto final. Los ejemplares quedan colocados en un espacio, ya sea bidimensional o tridimensional, de manera que las propias distancias nos indican su parecido. Pero más importante, los ejemplares se agrupan en grupos, también llamados conglomerados (también llamados clústeres). Cada ejemplar es asignado a un conglomerado. Estos conglomerados se forman en la medida en que algunos ejemplares tienen propiedades comunes y difieren de otros. En este texto hablaremos de cómo funciona el algoritmo K-Medias.Depto. de Psicobiología y Metodología en Ciencias del ComportamientoFac. de Psicologíaunpu