Abstract
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. © 2016 Association for Computational Linguistics.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, ACL 2016, August 7-12, 2016, Berlin, Germany, Volume 1: Long Papers |
| Pages | 1893-1902 |
| Volume | 4 |
| ISBN (Electronic) | 978-151082758-5 |
| Publication status | Published - 2016 |
| Event | 54th Annual Meeting of the Association for Computational Linguistics - Berlin, Germany Duration: 7 Aug 2016 → 12 Aug 2016 |
Conference
| Conference | 54th Annual Meeting of the Association for Computational Linguistics |
|---|---|
| Abbreviated title | ACL 2016 |
| Country/Territory | Germany |
| City | Berlin |
| Period | 7/08/16 → 12/08/16 |
Keywords
- Benchmarking
- Computational linguistics
- Linguistics
- Correlation analysis
- Editorial quality
- News articles