Creación de un conjunto de datos para el entrenamiento de un modelo de aprendizaje automático capaz de detectar noticias falsas de Colombia escritas en español desde la perspectiva del periodismo de datos

Abstract

Fake news represents a problem that is increasingly difficult to manage. Social networks and constant exposure to information make the task of determining the difference between true and false news a task impossible for humans to perform. In this context, it is necessary to adopt new technologies in the journalist's work; Artificial intelligence is a very useful tool. This project focuses on developing a data set of fake news written in Spanish that can be used to train a machine learning model capable of accurately classifying news. Creating a fake news dataset in Spanish is a significant challenge due to the need to guarantee the quality and representativeness of the data that allows training an effective model. For this, the bases proposed by data journalism will be available, this being an area where the knowledge of the journalist and data sciences converge.