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The 2016 United States presidential election was marked by the abuse oftargeted advertising on Facebook. Concerned with the risk of the same kind ofabuse to happen in the 2018 Brazilian elections, we designed and deployed anindependent auditing system to monitor political ads on Facebook in Brazil. Todo that we first adapted a browser plugin to gather ads from the timeline ofvolunteers using Facebook. We managed to convince more than 2000 volunteers tohelp our project and install our tool. Then, we use a Convolution NeuralNetwork (CNN) to detect political Facebook ads using word embeddings. Toevaluate our approach, we manually label a data collection of 10k ads aspolitical or non-political and then we provide an in-depth evaluation ofproposed approach for identifying political ads by comparing it with classicsupervised machine learning methods. Finally, we deployed a real system thatshows the ads identified as related to politics. We noticed that not allpolitical ads we detected were present in the Facebook Ad Library for politicalads. Our results emphasize the importance of enforcement mechanisms fordeclaring political ads and the need for independent auditing platforms.

Facebook Ads Monitor: An Independent Auditing System for Political Ads on Facebook