Soluções para coleta e tratamento de dados qualitativos sobre difusão e apropriação da Agenda 2030: a linguagem Python aplicada à construção de um corpus textual

Abstract

This article comes from a Scientific Initiation research Project at UFPB, with the objective of creating programming scripts to collect, clean, organize and analyze the textual corpus of the research. The project stems from understanding the importance of changing political discourse as an indicator of the domestic salience of international norms, in this case, the global development agenda expressed by the Sustainable Development Goals (SDGs). Initially, the research started with the effort to build an extensive database, containing all the speeches of the Presidents of the Republic of Brazil since 1985, a milestone of the country's redemocratization. As a conceptual apparatus, salience is understood as the variation in the legitimacy of international norms in a domestic context, measured through institutional, political and discourse or rhetoric changes. Dealing with such a long period, there was a change in the way of storing the collection of the Presidency of the Republic, which resulted in the need to create specific scripts to automate the collection and processing of data in an operational way for future analysis. As a result, this work describes the technologies developed, in the form of scripts in the Python language, for the construction of an extensive textual corpus, with more than six thousand speeches, and adaptable for future collection. In addition to overcoming the lack of standardization and systematization resulting from changes in government and technologies, the result shows a fruitful approximation between International Relations and other social sciences with elements of computing. Initially thought for the specific project, the merit of this research can be used for several other analyses, in an operational way, and easily adapted to modern software. Once the database was operationalized, the pre-reading of the material led to changes in the analysis intentions, which is why analysis scripts were not continued.