A Framework to Extract Arguments in Opinion Texts

In this article, the authors present foundational elements related to argument extraction in opinion texts with the objective to design a model of how consumers develop argumentation in such texts. A second goal is to analyze and synthesize user preferences and therefore user value systems from these arguments. They show that (1) within the context of opinionated expressions, a number of evaluative expressions with a ‘heavy’ semantic load receive an argumentative interpretation, and (2) that the association of an evaluative expression with a discourse structure such as an elaboration, an illustration, or a reformulation must also be interpreted as an argument. The authors develop a conceptual semantics of these discourse structures and show how they are analyzed using the Dislog programming language, running on the platform, dedicated to discourse analysis. DOI: 10.4018/jcini.2012070104 International Journal of Cognitive Informatics and Natural Intelligence, 6(3), 62-87, July-September 2012 63 Copyright © 2012, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. constitutes a relatively innovative step that should allow the capture of consumers underlying motivations. Besides the extraction of arguments, the open challenge remains the construction of a synthesis of the extracted arguments in natural language. Furthermore, a system of consumer preferences can be induced for each feature from these arguments. Given a recommendation (e.g., I strongly recommend it, do not stay here, go there if no alternative, etc.) and a list of attributes which are positively evaluated at various degrees (e.g., very well located, quite cheap) as well as another list of attributes which are negatively evaluated (not so clean, small rooms, quite noisy), it is possible to elaborate a system of user preferences or system of values. For a given consumer, it is indeed possible to identify his preferences: if the overall evaluation is positive, this roughly means that the positive attributes are globally more important than the negative ones. For a given product, on a larger scale, considering the pros and cons and the recommendations over a set of consumer evaluations, it is then possible to infer that some features are more essential than others, e.g., that localization and fares are more important than comfort for young consumers. In general, a system of values or preferences must be elaborated by consumer categories, e.g., by age and aims, since priorities may be different. From an application point of view, identifying arguments related to opinion expression and making a synthesis is of much importance for the service provider or decision-maker who can then focus on the criteria which need to be improved first. In this article, from a linguistic and cognitive point of view, we show that (1) within the context of opinion expression, a number of evaluative expressions, under the form of attributevalue pairs, where the value has a ’heavy’ semantic load, are interpreted as arguments, and (2) that the association of an evaluative expression with a discourse structure such as an elaboration, an illustration, or a reformulation must also be interpreted as an argument. These constructions are central to identify the why behind the evaluated statement. In this article we develop a global conceptual semantic representation for these constructions, since they need to be interpreted to infer user preferences and to construct a synthesis. We feel this is also an important step in this type of work, since a conceptual representation should allow the abstraction of natural language utterances, therefore allowing their interpretation, inference and synthesis. Finally, we show how an automatic recognition of these structures can be implemented in the Dislog programming language on the platform, dedicated to discourse analysis (Saint-Dizier, 2012).