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Evaluation in Discourse: a Corpus-Based Study
Author(s) -
Farah Benamara,
Nicholas Asher,
Yvette Yannick Mathieu,
Vladimir Popescu,
Baptiste Chardon
Publication year - 2016
Publication title -
dialogue and discourse
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.25
H-Index - 5
ISSN - 2152-9620
DOI - 10.5087/dad.2016.101
Subject(s) - computer science , sentence , natural language processing , linguistics , representation (politics) , sentiment analysis , annotation , polarity (international relations) , subjectivity , expression (computer science) , discourse analysis , corpus linguistics , artificial intelligence , task (project management) , political science , epistemology , philosophy , genetics , management , politics , biology , law , economics , cell , programming language
This paper describes the CASOAR corpus, the first manually annotated corpus that explores the impact of discourse structure on sentiment analysis with a study of movie reviews in French and in English as well as letters to the editor in French. While annotating opinions at the expression, the sentence or the document level is a well-established task and relatively straightforward, discourse annotation remains diffcult, especially for non experts. Therefore, combining both annotations poses several methodological problems that we address here. We propose a multi-layered annotation scheme that includes: the complete discourse structure according to the Segmented Discourse Representation Theory, the opinion orientation of elementary discourse units and opinion expressions, and their associated features. We detail each layer, explore the interactions between them and discuss our results. In particular, we examine the correlation between discourse and semantic category of opinion expressions, the impact of discourse relations on both subjectivity and polarity analysis and the impact of discourse on the determination of the overall opinion of a document. Our results demonstrate that discourse is an important cue for sentiment analysis, at least for the corpus genres we have studied.

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