%0 Conference Proceedings %T News Editorials: Towards Summarizing Long Argumentative Texts %A Syed, Shahbaz %A El Baff, Roxanne %A Kiesel, Johannes %A Al Khatib, Khalid %A Stein, Benno %A Potthast, Martin %Y Scott, Donia %Y Bel, Nuria %Y Zong, Chengqing %S Proceedings of the 28th International Conference on Computational Linguistics %D 2020 %8 December %I International Committee on Computational Linguistics %C Barcelona, Spain (Online) %F syed-etal-2020-news %X The automatic summarization of argumentative texts has hardly been explored. This paper takes a further step in this direction, targeting news editorials, i.e., opinionated articles with a well-defined argumentation structure. With Webis-EditorialSum-2020, we present a corpus of 1330 carefully curated summaries for 266 news editorials. We evaluate these summaries based on a tailored annotation scheme, where a high-quality summary is expected to be thesis-indicative, persuasive, reasonable, concise, and self-contained. Our corpus contains at least three high-quality summaries for about 90% of the editorials, rendering it a valuable resource for the development and evaluation of summarization technology for long argumentative texts. We further report details of both, an in-depth corpus analysis, and the evaluation of two extractive summarization models. %R 10.18653/v1/2020.coling-main.470 %U https://aclanthology.org/2020.coling-main.470 %U https://doi.org/10.18653/v1/2020.coling-main.470 %P 5384-5396