@inproceedings{StrussSiegelRuppenhoferetal.2019,
  author    = {Julia Maria Stru{\"s} and Melanie Siegel and Josef Ruppenhofer and Michael Wiegand and Manfred Klenner},
  title     = {Overview of GermEval Task 2, 2019 shared task on the identification of offensive language},
  series = {Preliminary proceedings of the 15th Conference on Natural Language Processing (KONVENS 2019), October 9 – 11, 2019 at Friedrich-Alexander-Universit{\"a}t Erlangen-N{\"u}rnberg},
  publisher = {German Society for Computational Linguistics \& Language Technology und Friedrich-Alexander-Universit{\"a}t Erlangen-N{\"u}rnberg},
  address   = {M{\"u}nchen [u.a.]},
  url       = {https://nbn-resolving.org/urn:nbn:de:bsz:mh39-93197},
  pages     = {352 -- 363},
  year      = {2019},
  abstract  = {We present the second edition of the GermEval Shared Task on the Identification of Offensive Language. This shared task deals with the classification of German tweets from Twitter. Two subtasks were continued from the first edition, namely a coarse-grained binary classification task and a fine-grained multi-class classification task. As a novel subtask, we introduce the classification of offensive tweets as explicit or implicit. The shared task had 13 participating groups submitting 28 runs for the coarse-grained task, another 28 runs for the fine-grained task, and 17 runs for the implicit-explicit task. We evaluate the results of the systems submitted to the shared task. The shared task homepage can be found at https://projects.fzai.h-da.de/iggsa/},
  language  = {en}
}