Exploratory Analysis of a New Corpus for Political Alignment Identification of Argentinian Journalists

Abstract

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.