Computational propaganda in Brazil : social bots during elections

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2017

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Computational propaganda can take the form of automated accounts (bots) spreading information, algorithmic manipulation and the spread of fake news to shape public opinion, amongst other methods. These techniques are being used in combination with the analysis and usage of large data sets of information about citizens held by corporations and governments. This form of propaganda is spreading to countries all over the world, most notably during the 2016 US presidential elections and the run-up to the UK's referendum to leave the European Union (Brexit). This working paper examines the use of computational propaganda in Brazil, the largest country in Latin America and a critical part of the global internet. This examination takes the form of the study of three recent cases of the use of computational propaganda in Brazil: the 2014 presidential elections, the impeachment of former president Dilma Rousseff and the 2016 municipal elections in Rio de Janeiro. It examines the legal framework governing the internet and the electoral process online, particularly how this process relates to computational propaganda. In addition, it seeks to understand how bots are involved in multifarious economic and political themes, and in ongoing debates in the country about corruption, privatization, and social and economic reform. Through a collection and analysis of hashtags related to major investigations into corruption in politics, as well as to proposed reforms to the social support systems and protests related to them, the working paper identifies bots that are involved in these debates and how they operate. Finally, it looks at potential responses to this kind of propaganda, from legal, technical and organizational perspectives, as well as at some indications of future trends in the use of these techniques in Brazilian society and politics.

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ARNAUDO, Dan. Computational propaganda in Brazil: social bots during elections. Computational Propaganda Research Project, Oxford, n. 2017.8, p. 2-38, 2017.

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