RESUMO Este artigo contém elementos ainda exploratórios de pesquisas que vêm sendo desenvolvidas pelos seus autores. São descritas algumas práticas colaborativas em redes ativistas, a exemplo do "Rio na Rua" e da "Avaaz", visando, sobretudo, exibir o estágio metodológico em que se encontra a pesquisa, para sustentar sua hipótese central: as redes colaborativas, politizadas ou não, mobilizam trabalho gratuito de bilhões de pessoas que servem, como qualquer trabalho não pago, para a acumulação de capital. Utilizamos o campo da Economia Política da Informação, Comunicação e Cultura (EPICC) como base teórica da análise e expomos resultados preliminares de pesquisas empíricas em andamento.Palavras-chave: Mais-valia 2.0; Trabalho Gratuito; Redes de Mobilização; Facebook; Avaaz.ABSTRACT This article brings a preliminary study that has been carried on by its authors in the last months. We describe collaborative practices in activist networks, such as Rio na Rua's Facebook page and "Avaaz". The main focus here is to present the methodological phase of the research to support our thesis: collaborative networks, whether political or not, mobilize non-paid work of billions of people who contribute to capital accumulation. The Political Economy of Information, Communication and Culture is the theoretical basis of the analisys and we publish here some preliminary results of ongoing empirical research.Keywords: Surplus value 2.0; Non-paid work; Mobilization Networks; Facebook; Avaaz.
We present a data-driven analyses of activist media produced by inhabitants of the favelas of Rio de Janeiro. The content was collected using their Facebook pages from 2015 to 2017 and was analyzed through computational and manual methods. The analyses reiterate and extend previous research, showing that the collectives are focused on the particular favela's identity and the demand for rights mainly-but not only-linked to violence, police abuses and state racism. It also presents nontrivial process to look at data produced by media collectives on social networks, by analyzing their posts in an aggregated way through clustering techniques, rather than relying on a few popular posts that may or may not represent their main agenda.
Automatic topic detection in document collections is an important tool for various tasks. In particular, it is valuable for studying and understanding socio-political phenomena. A currently relevant example is the automatic analysis of streams of posts issued by different activist groups in the current Brazilian turmoil, through the analysis of the generated streams of texts published on the web. It is useful to determine the relative importance of the different topics identified. We can find in the literature proposals for measuring topic relevance. In this paper, we adopt two of such measures and apply them to data sets extracted from Facebook pages related to Brazilian political activism. On top of the analysis, we then carry an experimental evaluation of the human interpretability for these two measures by comparing their outcomes with the opinion of three Brazilian professionals from the field of Communication Science and media-activists.
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