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A field that is gaining interest in Data Mining is author profiling, the identification of patterns shared by a group of people. It includes classification problems of Web's users according to their age, gender, and political alignment, among others. This report addresses the political alignment identification problem, an author profiling task that aims at identifying political bias/orientation in people's writings. As usual in any automatic text analysis, a critical aspect here is having available adequate data sets so that the data mining and machine learning methods can obtain reliable and informative results. Thus, the experimental work uses a new corpus for the study of political alignment in documents of Argentinean journalists. The study also includes several kinds of analysis of documents of pro-government and opposition journalists such as the relevance of terms in each journalist class, sentiment analysis, topic modeling and the analysis of psycholinguistic indicators obtained from the Linguistic Inquiry and Word Count (LIWC) system. From the experimental results, interesting patterns could be observed such as the topics both types of journalists write about, how the sentiment polarities are distributed and how the writings of pro-government and opposition journalists differ in the distinct LIWC categories. ; En la Minería de Datos, un área que ha ganado interés es la determinación del perfil del autor, que identifica patrones compartidos por un grupo de personas y aborda problemas de clasificación de los usuarios de la Web de acuerdo a edad, género, orientación política, etc. En este informe, se tomará como caso de estudio la tarea de identificación de la alineación política, la cual tiene como objetivo determinar a partir de los escritos de las personas el sesgo político. En este tipo de campo, un aspecto clave es disponer un conjunto de datos adecuados para que los procesos de minería de datos y aprendizaje automático puedan obtener resultados confiables. Para ello, se realiza la experimentación sobre un corpus para el estudio de la alineación política en documentos de periodistas argentinos. El estudio incluye varios tipos de análisis de documentos de periodistas opositores y progubernamentales, como ser la relevancia de los términos en cada clase de documentos, el análisis de sentimientos, el modelado de tópicos y el análisis de indicadores psicolingüísticos obtenidos del sistema LIWC. En los resultados experimentales, se pueden observar patrones interesantes, como por ejemplo los tópicos sobre los que escriben ambos tipos de periodistas, cómo se distribuyen las polaridades de los sentimientos y cómo los escritos de los periodistas progubernamentales y periodistas opositores difieren en las distintas categorías de LIWC.

Political alignment identification is an author profiling task that aims at identifying political bias/orientation in people' writings. As usual in any automatic text analysis, a critical aspect here is having available adequate data sets so that the data mining and machine learning approaches can obtain reliable and informative results. This article makes a contribution in this regard by presenting a new corpus for the study of political alignment in documents of Argentinian journalists. The study also includes several kinds of analysis of documents of pro-government and opposition journalists such as the relevance of terms in each journalist class, sentiment analysis, topic modelling and the analysis of psycholinguistic indicators obtained from the Linguistic Inquiry and Word Count (LIWC) system. From the experimental results, interesting patterns could be observed such as the topics both types of journalists write about, how the sentiment polarities are distributed and how the writings of pro-government and opposition journalists differ in the distinct LIWC categories. ; Facultad de Informática

Political alignment identification is an author profiling task that aims at identifying political bias/orientation in people' writings. As usual in this kind of field, a key aspect is to have available adequate data sets so that the data mining and machine learning approaches can obtain reliable and informative results. This article takes a step in this direction by introducing a new corpus for the study of political alignment in documents of Argentinian journalists. The study also includes several kinds of analysis of documents of pro-government and opposition journalists such as sentiment analysis, topic modelling and the analysis of psycholinguistic indicators obtained from the Linguistic Inquiry and Word Count (LIWC) system. From the experimental results, interesting patterns could be observed such as the topics both types of journalists write about, how the sentiment polarities are distributed and how the writings of pro-government and opposition journalists differ in the distinct LIWC categories. ; XVI Workshop Bases de Datos y Minería de Datos. ; Red de Universidades con Carreras en Informática