Abstract

This research has two main goals: i) to compare how Chilean and Spanish news outlets discuss fake news, and ii) to propose a mixed methodology, combining data science and content analysis methods in order to understand how this journalistic treatment is done. To build the corpus analyzed on this study, we used a crawler that followed Chilean and Spanish news outlets in Twitter, and on top of that large dataset (over than 2 million tweets per year, per country), we searched for a set of keywords appearing on the headings or snippets of the news linked to those tweets. We obtained 663 pieces of news, and editorial columns from the Chilean data, and 466 pieces of news from the Spanish data coming from 50 news sources, from January 2017 to December 2019. From our analysis, we concluded that the journalistic treatment is similar in both countries in several dimensions. However, the Spanish news sources make more efforts in trying to educate the audience to identify fake news.