@InProceedings{sadeque-EtAl:2019:S19-1,
  author    = {Sadeque, Farig  and  Rains, Stephen  and  Shmargad, Yotam  and  Kenski, Kate  and  Coe, Kevin  and  Bethard, Steven},
  title     = {Incivility Detection in Online Comments},
  booktitle = {Proceedings of the Eighth Joint Conference on Lexical and Computational Semantics (*SEM 2019)},
  month     = {June},
  year      = {2019},
  address   = {Minneapolis, Minnesota},
  publisher = {Association for Computational Linguistics},
  pages     = {283--291},
  abstract  = {Incivility in public discourse has been a major concern in recent times as it can affect the quality and tenacity of the discourse negatively. In this paper, we present neural models that can learn to detect name-calling and vulgarity from a newspaper comment section. We show that in contrast to prior work on detecting toxic language, fine-grained incivilities like namecalling cannot be accurately detected by simple models like logistic regression. We apply the models trained on the newspaper comments data to detect uncivil comments in a Russian troll dataset, and find that despite the change of domain, the model makes accurate predictions.},
  url       = {http://www.aclweb.org/anthology/S19-1031}
}