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  1. IGGSA-STEPS: Shared Task on Source and Target Extraction from Political Speeches
    Erschienen: 2016
    Verlag:  Institut für Deutsche Sprache, Bibliothek, Mannheim

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    Quelle: DNB Sachgruppe Deutsche Sprache und Literatur
    Beteiligt: Struß, Julia Maria (Verfasser); Wiegand, Michael (Herausgeber); Remus, Robert (Herausgeber); Gindl, Stefan (Herausgeber)
    Sprache: Englisch
    Medientyp: Unbestimmt
    Format: Online
    Weitere Identifier:
    Übergeordneter Titel: In: Journal for Language Technology and Computational Linguistics . 29, 2014., 1., S. 33-46
    Schlagworte: Korpus <Linguistik>; Annotation; Parlamentsdebatte; Data Mining; Politische Sprache; Automatische Sprachanalyse
    Weitere Schlagworte: selection of textual sources; annotation guidelines; gold standard corpus
    Umfang: Online-Ressource
  2. IGGSA-STEPS: Shared Task on Source and Target Extraction from Political Speeches
  3. IGGSA-STEPS: Shared Task on Source and Target Extraction from Political Speeches
    Erschienen: 2016
    Verlag:  Institut für Deutsche Sprache, Bibliothek, Mannheim

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    Quelle: Verbundkataloge
    Beteiligt: Struß, Julia Maria (Verfasser); Wiegand, Michael (Herausgeber); Remus, Robert (Herausgeber); Gindl, Stefan (Herausgeber)
    Sprache: Englisch
    Medientyp: Buch (Monographie)
    Format: Online
    Weitere Identifier:
    DDC Klassifikation: Germanische Sprachen; Deutsch (430)
    Schlagworte: Korpus <Linguistik>; Annotation; Parlamentsdebatte; Data Mining; Politische Sprache; Automatische Sprachanalyse
    Weitere Schlagworte: selection of textual sources; annotation guidelines; gold standard corpus
    Umfang: Online-Ressource
    Bemerkung(en):

    In: Journal for Language Technology and Computational Linguistics . 29, 2014., 1., S. 33-46

  4. MLSA – A Multi-layered Reference Corpus for German Sentiment Analysis

    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... mehr

     

    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.

     

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    Quelle: BASE Fachausschnitt Germanistik
    Sprache: Englisch
    Medientyp: Konferenzveröffentlichung
    Format: Online
    DDC Klassifikation: Linguistik (410)
    Schlagworte: Deutsch; Korpus
    Lizenz:

    rightsstatements.org/page/InC/1.0/ ; info:eu-repo/semantics/openAccess