Discourse Segmentation of Opinion Texts

Abstract

[contribution to the panel Nonveridicality, evaluation and coherence relations, organized by Taboada Maite]International audienceThe extraction of elementary opinion expressions from texts has been much studied during the last decade. Actually, there are relatively effective algorithms for extracting and summarising opinions ((Hatzivassiloglou and McKeown, 1997)(Vernier et al., 2009)). However, as (Polanyi and Zaenen, 2006) stated, identifying prior polarity alone may not suffice to improve sentiment analysis at a finer-grain. Indeed, discourse structure can influence the interpretation of an evaluation both at the clause level, where opinions can be disambiguated, and at the document level, where rhetorical relations can be used to improve the recognition of the overall stance. A computational approach to the discourse analysis of opinion expressions has been recently explored in (Somasundaran, 2009). This work uses two sets of discourse-level relations: relations between targets of opinions, and between opinions themselves. However, this work does not refer to any well-known discourse theory and does not study how discourse segments conveying opinion expressions interact with non opinion discourse segments. The work described in this paper follows (Asher et al., 2009) where Segmented Discourse Representation Theory (SDRT, Asher and Lascarides, 2003) is used in order to get a deeper understanding of contextual polarity. Our aim is to study what are the impact of some discourse relations to compute the strength of opinions, more precisely - how the degree of commitment and the degree of veracity that underline the attribution relation act on an opinion, as in: “Peter affirmed that the owner of the restaurant has changed last year, and thus the quality of the food has significantly dropped.” - how can we analyse opinions that are in the scope of a hypothesis or a condition. - how contrasts influence opinion polarity within a clause. - how a discourse segment conveying an implicit opinion can be disambiguated, as in : “This restaurant is really nice, but has no terrace.” - how the discourse graph can be used to compute the overall opinion To reach this goal, automatically detecting discourse segments is an important preliminary step. We propose an approach to opinion discourse segmentation that allows for identifying elementary opinion units. This enables us to define a projection of the relations from the discourse segments level to the opinion level. Moreover, the granularity of the segmentation allows the detection of relations within syntactic constituents like verb phrases, such as the contrast in “This restaurant is good but expensive.” Our segmenter is developed on the top of the discourse segmenter (Afantenos et al, 2010) of the French ANNODISproject (an ongoing effort to create a discourse bank for French). We use a set of rules that refine the ANNODIS segments using syntactic and semantic features, such as coordination words or contrast marquers