An Evaluation of Structural Characteristics of Networks to Identify Media Bias in News Portals - Aires, Victória Patrícia; Silva, Altigran Soares da; Nakamura, Fabíola Guerra; Nakamura, Eduardo Freire (Proceedings of the Brazilian Symposium on Multimedia and the Web (WebMedia), 2020)
Nowadays, news websites are the main sources of information for most people. But these outlets may have a bias in their publications, favoring some ideology. This can influence people's opinion regarding several topics. Methods to automatically detect bias are usually based on aspects such as text and embedded hyperlinks. In this work, we present a strategy to detect media bias by analyzing networks that model citations between news websites, evaluating if the bias is related to structural characteristics of these networks. We show that ideological bias can be captured by citation patterns and present a method that uses these patterns to automatically identify political bias in news websites, reaching accuracy and F1 scores above 72% and 0.70, respectively.