@article{KruegerLukowiakSonntagetal.2017,
  author    = {Kr{\"u}ger, K. R. and Lukowiak, A. and Sonntag, J. and Warzecha, Saskia and Stede, Manfred},
  title     = {Classifying news versus opinions in newspapers},
  series = {Natural language engineering},
  volume    = {23},
  journal   = {Natural language engineering},
  publisher = {Cambridge Univ. Press},
  address   = {Cambridge},
  issn      = {1351-3249},
  doi       = {10.1017/S1351324917000043},
  pages     = {687 -- 707},
  year      = {2017},
  abstract  = {Newspaper text can be broadly divided in the classes 'opinion' (editorials, commentary, letters to the editor) and 'neutral' (reports). We describe a classification system for performing this separation, which uses a set of linguistically motivated features. Working with various English newspaper corpora, we demonstrate that it significantly outperforms bag-of-lemma and PoS-tag models. We conclude that the linguistic features constitute the best method for achieving robustness against change of newspaper or domain.},
  language  = {en}
}