A Review Corpus for Argumentation Analysis

  • Henning Wachsmuth
  • Martin Trenkmann
  • Benno Stein
  • Gregor Engels
  • Tsvetomira Palakarska
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8404)


The analysis of user reviews has become critical in research and industry, as user reviews increasingly impact the reputation of products and services. Many review texts comprise an involved argumentation with facts and opinions on different product features or aspects. Therefore, classifying sentiment polarity does not suffice to capture a review’s impact. We claim that an argumentation analysis is needed, including opinion summarization, sentiment score prediction, and others. Since existing language resources to drive such research are missing, we have designed the ArguAna TripAdvisor corpus, which compiles 2,100 manually annotated hotel reviews balanced with respect to the reviews’ sentiment scores. Each review text is segmented into facts, positive, and negative opinions, while all hotel aspects and amenities are marked. In this paper, we present the design and a first study of the corpus. We reveal patterns of local sentiment that correlate with sentiment scores, thereby defining a promising starting point for an effective argumentation analysis.


Product Feature Sentiment Analysis Positive Opinion Negative Opinion Argumentation Analysis 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Henning Wachsmuth
    • 1
  • Martin Trenkmann
    • 2
  • Benno Stein
    • 2
  • Gregor Engels
    • 1
  • Tsvetomira Palakarska
    • 2
  1. 1.s-lab – Software Quality LabUniversität PaderbornPaderbornGermany
  2. 2.Bauhaus-Universität WeimarWeimarGermany

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