Summary of the paper

Title Annotating Opinions in German Political News
Authors Hong Li, Xiwen Cheng, Kristina Adson, Tal Kirshboim and Feiyu Xu
Abstract This paper presents an approach to construction of an annotated corpus for German political news for the opinion mining task. The annotated corpus has been applied to learn relation extraction rules for extraction of opinion holders, opinion content and classification of polarities. An adapted annotated schema has been developed on top of the state-of-the-art research. Furthermore, a general tool for annotating relations has been utilized for the annotation task. An evaluation of the inter-annotator agreement has been conducted. The rule learning is realized with the help of a minimally supervised machine learning framework DARE.
Topics Corpus (creation, annotation, etc.), Tools, systems, applications, Emotion Recognition/Generation
Full paper Annotating Opinions in German Political News
Bibtex @InProceedings{LI12.640,
  author = {Hong Li and Xiwen Cheng and Kristina Adson and Tal Kirshboim and Feiyu Xu},
  title = {Annotating Opinions in German Political News},
  booktitle = {Proceedings of the Eight International Conference on Language Resources and Evaluation (LREC'12)},
  year = {2012},
  month = {may},
  date = {23-25},
  address = {Istanbul, Turkey},
  editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Mehmet Uğur Doğan and Bente Maegaard and Joseph Mariani and Asuncion Moreno and Jan Odijk and Stelios Piperidis},
  publisher = {European Language Resources Association (ELRA)},
  isbn = {978-2-9517408-7-7},
  language = {english}
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