Abstract
To perform aspect-level sentiment analysis, in the context of customer reviews, it is necessary to deal not only with subjective opinions, that are well covered by literature, but also with fact-implied opinions, that are less examined since they are less common and harder to handle. This work focuses on a specific type of fact-based opinion called producing and consuming expression. For example, expressions like “this printer consumes a lot of ink” and “this washing-machine makes a lot of noise” are instances of this type of opinion. This research aims to build a tool that can identify these expressions, classify their sentiment polarities and determine their opinion targets. To achieve this task, we started analyzing these expressions from a linguistic point of view. Then we developed a set of linguistic resources using the Nooj software. This set consists of one dictionary and one grammar. The dictionary contains verbs that express usage and production; adjectives and determiners that modify quantity, size, etc. and some generic nouns of resources and wastes. The grammar can recognize and tags simple and complex sentences that are producing and consuming expressions. This grammar produces a tag that allows to determine the sentiment of the expression simply by applying the rules of sentiment composition.