@InProceedings{kevin-EtAl:2018:FEVER,
  author    = {Kevin, Vincentius  and  Högden, Birte  and  Schwenger, Claudia  and  Sahan, Ali  and  Madan, Neelu  and  Aggarwal, Piush  and  Bangaru, Anusha  and  Muradov, Farid  and  Aker, Ahmet},
  title     = {Information Nutrition Labels: A Plugin for Online News Evaluation},
  booktitle = {Proceedings of the First Workshop on Fact Extraction and VERification (FEVER)},
  month     = {November},
  year      = {2018},
  address   = {Brussels, Belgium},
  publisher = {Association for Computational Linguistics},
  pages     = {28--33},
  abstract  = {In this paper we present a browser plugin NewsScan that assists online news readers in evaluating the quality of online content they read by providing information nutrition labels for online news articles. In analogy to groceries, where nutrition labels help consumers make choices that they consider best for themselves, information nutrition labels tag online news articles with data that help readers judge the articles they engage with. This paper discusses the choice of the labels, their implementation and visualization.},
  url       = {http://www.aclweb.org/anthology/W18-5505}
}