JornalisTA (UFRJ), com mais de 10 anos de especialização em digital; Mestra em Comunicação e Cultura com ênfase em tecnologias da comunicação (ECO/UFRJ); PhD em Mídias Digitais (Faculdade de Engenharia Informática/U.Porto); pós-doc em Comunicação & Internet (ECO/UFRJ). CV Lattes: http://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4337341Z9 Supervisors: Rose Marie Santini
En este trabajo se presenta un análisis de datos basado en medios activistas de habitantes de fav... more En este trabajo se presenta un análisis de datos basado en medios activistas de habitantes de favelas de Río de Janeiro. El contenido se recopiló en páginas de Facebook desde 2015 a 2017 y se analizó a través de métodos computacionales y manuales. El estudio reitera y amplía investigaciones anteriores, que muestran que los colectivos se centran en la identidad de la favela y la demanda de derechos, principalmente los relacionados con la violencia, los abusos policiales y el racismo estatal. Además, se propone un proceso no trivial para analizar los datos de los colectivos de medios en las redes sociales a través de técnicas de agrupación (clustering), en lugar de analizar unas cuantas publicaciones populares que pueden no representar su agenda principal. / 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.
This work investigates the Journeys of June of 2013, in Brazil, with a special focus on the distr... more This work investigates the Journeys of June of 2013, in Brazil, with a special focus on the distributed and transient leadership of the movement, the ideological spectra that it represented and the technopolitical nature of such events. We present a longitudinal analysis based on data from surveys (n=579) and 252 Facebook activist pages (n=684,361 posts) from the Right, the Traditional Left, and the Post-June Left networks, uncovering a five-year timeframe. We also propose a multi-method approach for longitudinal studies on network-movements, in which we cross the survey’s results with Facebook data using data mining and information extraction techniques, particularly the automated topic modeling with the LDA algorithm. We also propose to use the “engagement per topic” as a useful metric to determine pages’ influence, from a non-trivial perspective of the data, thus escaping from analyses merely based on single posts’ relevance and making the social data more robust for scientific research. We consider the June movement as a technopolitical event, one which used hybrid spaces (simultaneously taking place online and offline) to foster political participation across the ideological spectrum. Therefore, this multi-method perspective was crucial to uncover the movement’s multi-layering practices. We have learned that different leftist movements fostered the Journeys and motivated the transient leading roles, which ended up opening room for the right-leaning agenda during June 2013.
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Papers by Marcela Canavarro
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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.