A Review Corpus for Argumentation Analysis

authored by

Henning Wachsmuth, Martin Trenkmann, Benno Stein, Gregor Engels, Tsvetomira Palakarska

Abstract

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.

External Organisation(s)

Paderborn University
Bauhaus-Universität Weimar

Type

Conference contribution

Pages

115-127

No. of pages

13

Publication date

2014

Publication status

Published

Peer reviewed

Yes

ASJC Scopus subject areas

Theoretical Computer Science, Computer Science(all)

Electronic version(s)

https://doi.org/10.1007/978-3-642-54903-8_10 (Access: Closed)