@inproceedings{ClematideGrindlKlenneretal.2016,
  author    = {Simon Clematide and Stefan Grindl and Manfred Klenner and Stefanos Petrakis and Robert Remus and Josef Ruppenhofer and Ulli Waltinger and Michael Wiegand},
  title     = {MLSA – A Multi-layered Reference Corpus for German Sentiment Analysis},
  series = {Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12). Istanbul, Turkey},
  publisher = {European Language Resources Association},
  isbn      = {978-2-9517408-7-7},
  url       = {https://nbn-resolving.org/urn:nbn:de:bsz:mh39-52345},
  pages     = {3551 -- 3556},
  year      = {2016},
  abstract  = {In this paper, we describe MLSA, a publicly available multi-layered reference corpus for German-language sentiment analysis. The construction of the corpus is based on the manual annotation of 270 German-language sentences considering three different layers of granularity. The sentence-layer annotation, as the most coarse-grained annotation, focuses on aspects of objectivity, subjectivity and the overall polarity of the respective sentences. Layer 2 is concerned with polarity on the word- and phrase-level, annotating both subjective and factual language. The annotations on Layer 3 focus on the expression-level, denoting frames of private states such as objective and direct speech events. These three layers and their respective annotations are intended to be fully independent of each other. At the same time, exploring for and discovering interactions that may exist between different layers should also be possible. The reliability of the respective annotations was assessed using the average pairwise agreement and Fleiss’ multi-rater measures. We believe that MLSA is a beneficial resource for sentiment analysis research, algorithms and applications that focus on the German language.},
  language  = {en}
}