Nem tão #simples assim

Abstract

Para fazer o monitoramento do debate público em redes sociais, a FGV/DAPP lança mão de um conjunto de metodologias e procedimentos de pesquisa, fazendo articulação entre as áreas de Linguística, Sociologia, Comunicação, Estatística e Tecnologia da Informação. É necessária essa integração de domínios para que seja possível não apenas extrair e organizar o enorme volume de dados da internet, como para qualificar e compreender a percepção social com rigor científico e respeito à relevância das redes sociais — em especial o Twitter e o Facebook — para a sociedade brasileira. O núcleo de análise de redes sociais da FGV/DAPP se ocupa em acompanhar as discussões da sociedade e em realizar recortes de pesquisa sobre quaisquer assuntos de políticas públicas — objeto que está na essência do propósito da FGV/DAPP.

The social network analysis team at FGV/DAPP is responsible for monitoring the discussions of the society and for carrying out research on any topics regarding public policies — the object that is the essence of the purpose of FGV/DAPP. That is, focusing on debates in the national and international levels, or even in the regional level, about, for example, public security, immigration, health, mobility, education and politics. Considering the consolidation of a network society (CASTELLS, 2009), created by the so-called information revolution, the monitoring and analysis of social networks takes on a role of great relevance for better understanding the political behavior of Brazilians (and of the main social actors on the networks), and becomes a productive methodology for political analysis. In this document, we present some already finished studies, explaining in detail the process of data collection and research that we propose as a vector for understanding the public opinion and the social interests highlighted in the vast universe of the internet. Dealing with large quantities of data is always a challenge, and a rigorous methodology is necessary for such an undertaking, so that we are able to analyze its possible social and political implications. Complex networks such as the ones we analyze have been studied by various fields of knowledge, specifically the identification of communities in computing and in the graph theory (ELHADI; AGAM, 2013; LEE; CUNNINGHAM, 2013;MILKOV et al., 2006). It is a mixture of visual and statistical analysis that use algorithms of the free software Gephi (BASTIAN et al., 2009). The first challenge after establishing the words that will guide the data collection is trying to detect the different groups. We argue in this study that the groups found in the discussions in social networks can be understood as a virtual layer of the collective subjectivities as envisioned by Domingues (1995, 1999).This argument is based on the empirical finding that clustering algorithms dividea network of retweets in groups of distinct opinions (CONOVER et al., 2011). First, we will explain what collective subjectivities are, and then we will detail the research methodology