Metalearning

Roaa Al Feel, an early-career researcher, discusses her passion for using data science for social good. She uses data to reflect living conditions of society, and in the paper published with Patterns in November, the team explores machine learning techniques for the detection of fake news around the Syrian war, demonstrating the efficacy of meta-learning techniques when tackling datasets of a modest size.
In this article, we pursue the automatic detection of fake news reporting on the Syrian war using machine learning and meta-learning. The proposed approach is based on a suite of features that include a given article's linguistic style; its level of subjectivity, sensationalism, and sectarianism; the strength of its attribution; and its consistency with other news articles from the same “media camp”. To train our models, we use FA-KES, a fake news dataset about the Syrian war.