En el año 2016 estaba buscando un nuevo campo de investigación, interesado en PLN orientado a la política, comenté con un compañero mis inquietudes y me dijo que la Dra. Isabel Sánchez Berriel trabajaba en ese campo. Me puse en contacto con ella, con sus directivas y con el estado del arte en este campo (Messina Group, Schmidt Futures,...), pronto comenzamos a crear un sistema sobre deeplearning con un kernel de una red neuronal para hacer estimaciones electorales en base a redes sociales, periódicos, etc. Para que detectara correctamente el idioma con la herramienta Freeling, añadimos a la base de datos (MongoDB) de conocimiento: el texto de la Wikipedia, libros y novelas de diferentes autores, artículos de periódicos,... Terabytes de texto plano en español.
El sistema comenzó en el año 2016 a capturar tweets con la API Twitter4j de un conjunto de cuentas semilla pero con un subsistema de estrella que iba captando cuentas de manera exponencial fundamentándose en los followers y en los followers de los followers... pero con la etiqueta de capturar las cuentas de zonas cercanas a un punto geográfico, de tal manera se podría tener el análisis de sentimiento de las personas que estaban en una zona en concreto: un barrio, un municipio, una isla, una comunidad autónoma,...
Tras dos años de ardua investigación, desarrollo e implementación, en mayo de 2018 publicamos la primera versión en el X Congreso Internacional de Lingüística del Corpus celebrado en Extremadura con el trabajo Técnicas de aprendizaje profundo aplicadas al análisis visual de colocaciones léxicas en español.
En este mismo año 2018, se une a nuestro grupo de investigación la Dra. María del Pilar García Díaz de la Universidad Alcalá de Henares de Madrid que añade a nuestro sistema, técnicas de neuroevolución dando unos resultados excepcionales. Y presentamos el artículo Neuroevolution techniques applied in the processing of natural language through deep learning for the analysis of texts related to the experiences in tourist destinations a las ayudas de la fundación de BBVA a los equipos de investigación.
- La religión sigue decreciendo entre las personas más jóvenes y mayoritariamente los ateos votan a partidos de izquierda.
- Se imputan los indecisos en base a la probabilidad asignada por un modelo de Maching Learning que se entrena con variables como barrio, nivel de estudios, edad, sexo, grupo ideológico o recuerdo de voto.
- Este proyecto no incluye la variación de los indecisos en base al estudio de campaña electoral.
- Este proyecto no incluye ponderación de votos, por tanto, se asignará cada concejal por cada X votos.
- Con las cuentas capturas se ha aplicado la formula del muestreo probabilístico (muestreo estatificado) para determinar las asignaciones a cada partido.
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