Automatic Detection of Opposition Relations in Legal Texts Using Sentiment Analysis Techniques: A Case Study

The documentation that describes the regulations within a Society, is oriented towards specific areas. This fact does not prevent maintaining concordance in the temporality and transversality of the documents. This work defines the concept of "opposition relations" in legal texts. We identify entities and evaluate the polarity of each paragraph with sentiment analysis techniques. If an entity appears in different paragraphs (articles of law) with opposite polarities, we evaluate the entity’s contexts. We look for antonyms between the words that give polarity to the opposite paragraphs. If there is an antonymic relation in words associated with the entity, we have an opposition relation. The described methodology analyzes the relationship of entities in Mexican Environmental Laws, and the study is oriented towards coherence in the legislation for sustainable development. This process was implemented by computational processing, which required the transformation of current Mexican laws, unifying its structure. Eight environmental laws were analyzed, 1920 entities were identified that appear more than once; 44 of them were identified with opposite polarities, due to their context, a detailed analysis of two cases with potential opposite relationships is exemplified.