Downloads provided by UsageCounts
Newer Version of this corpus in the 2018 version can be found here: https://doi.org/10.5281/zenodo.1340629 The Webis-Editorials-16 corpus is a novel corpus with 300 news editorials evenly selected from three diverse online news portals: Al Jazeera, Fox News, and The Guardian. The aim of the corpus is to study (1) the mining and classification of fine-grained types of argumentative discourse units and (2) the analysis of argumentation strategies pursued in editorials to achieve persuasion. To this end, each editorial contains manual type annotations of all units that capture the role that a unit plays in the argumentative discourse, such as assumption or statistics. The corpus consists of 14,313 units of six different types, each annotated by three professional annotators from the crowdsourcing platform upwork.com.
{"references": ["Khalid Al-Khatib, Henning Wachsmuth, Johannes Kiesel, Matthias Hagen, and Benno Stein. A News Editorial Corpus for Mining Argumentation Strategies. In 26th International Conference on Computational Linguistics (COLING 2016), pages 3433-3443, December 2016. Association for Computational Linguistics"]}
arguments, 2016, news editorials, news, argumentation strategies, argumentative discourse units
arguments, 2016, news editorials, news, argumentation strategies, argumentative discourse units
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
| views | 64 | |
| downloads | 14 |

Views provided by UsageCounts
Downloads provided by UsageCounts