Doris Martin at SemEval-2019 Task 4: Hyperpartisan News Detection with Generic Semi-supervised Features
Rodrigo Agerri · 2019
In this paper we describe our participation to the Hyperpartisan News Detection shared task at SemEval 2019.Motivated by the late arrival of Doris Martin, we test a previously developed document classification system which consists of a combination of clustering features implemented on top of some simple shallow local features.We show how leveraging distributional features obtained from large in-domain unlabeled data helps to easily and quickly develop a reasonably good performing system for detecting hyperpartisan news.The system and models generated for this task are publicly available.