Fine-Grained News Classification

Abstract

This thesis investigates the concepts of fine-grained news classification. To do this, an empirical study in which human annotators categorized news was conducted. The also study consisted of measuring agreement between hu- man annotators and evaluating the precision of the annotations. The study revealed a need for a framework for fine-grained news classification. A framework was then developed and evaluated, producing a complete annotated dataset.