Linguistic Benchmarks of Online News Article Quality
Online news editors ask themselves the same question many times: what is missing in this news article to go online? This is not an easy question to be answered by computational linguistic methods. In this work, we address this important question and characterise the constituents of news article editorial quality. More specifically, we identify 14 aspects related to the content of news articles. Through a correlation analysis, we quantify their independence and relation to assessing an article’s editorial quality. We also demonstrate that the identified aspects, when combined together, can be used effectively in quality control methods for online news.