An Analysis of Subjectivity in Brazilian News - Lima, D. F.; Melo, A. S. C.; Marinho, L. B. (Anais do Symposium on Knowledge Discovery, Mining and Learning (KDMiLe), 2019)
With the advent of digital journalism, the democratization of information has become a reality, since news articles are published as soon as the facts occur and are accessible from any device connected to the internet. It is common sense the perception that some newspapers are more biased than others when it comes to the way of exposing the facts. However, automatic ways of measuring such biases is still an open research challenge. Under the premise that journalistic texts must have objective and unbiased language, news with high levels of subjectivity may indicate bias. In this paper, we propose to use subjectivity lexicons to characterize subjectivity in five news portals that are popular in Brazil. To better understand the results found, we performed a correlation analysis between the levels of subjectivity found and readability and news popularity metrics. We believe that the methods we used along with our findings contribute to a better understanding of the linguistic characteristics of the news we consume daily.