Browsing by Subject "Authorship analysis"

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    Producción científica española en turismo: Un análisis de autoría basado en revistas internacionales con alto impacto y visibilidad
    (Murcia: Servicio de Publicaciones de la Universidad de Murcia, 2018) López Bonilla, José Manuel; Granados Perea, Concepción; López Bonilla, Luis Miguel
    El presente estudio se ha centrado en el análisis de la producción científica con difusión internacional de los autores afiliados a instituciones españolas. La búsqueda se ha realizado a través de la base de datos de Scopus durante el período 2002-2013. Especialmente, se han analizado los trabajos publicados en revistas científicas que están incluidas en el Journal Citation Reports (JCR). Entre otros hallazgos, hay una gran concentración de autores que pertenecen a los ámbitos de la economía y la empresa. Las revistas científicas más utilizadas han sido Tourism Management y Tourism Economics.
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    Psychographic traits identification based on political ideology: an author analysis study on Spanish politicians’ tweets posted in 2020
    (Elsevier, 2022-05) García Díaz, José Antonio; Colomo Palacios, Ricardo; Valencia García, Rafael; Informática y Sistemas; Facultades de la UMU::Facultad de Informática
    In general, people are usually more reluctant to follow advice and directions from politicians who do not have their ideology. In extreme cases, people can be heavily biased in favour of a political party at the same time that they are in sharp disagreement with others, which may lead to irrational decision making and can put people’s lives at risk by ignoring certain recommendations from the authorities. Therefore, considering political ideology as a psychographic trait can improve political micro-targeting by helping public authorities and local governments to adopt better communication policies during crises. In this work, we explore the reliability of determining psychographic traits concerning political ideology. Our contribution is twofold. On the one hand, we release the PoliCorpus-2020, a dataset composed by Spanish politicians’ tweets posted in 2020. On the other hand, we conduct two authorship analysis tasks with the aforementioned dataset: an author profiling task to extract demographic and psychographic traits, and an authorship attribution task to determine the author of an anonymous text in the political domain. Both experiments are evaluated with several neural network architectures grounded on explainable linguistic features, statistical features, and state-of-the-art transformers. In addition, we test whether the neural network models can be transferred to detect the political ideology of citizens. Our results indicate that the linguistic features are good indicators for identifying fine-grained political affiliation, they boost the performance of neural network models when combined with embedding-based features, and they preserve relevant information when the models are tested with ordinary citizens. Besides, we found that lexical and morphosyntactic features are more effective on author profiling, whereas stylometric features are more effective in authorship attribution.