Visibilidade no Facebook: Modelos, Medições e Implicações
Facebook news feed personalization algorithm has a significant impact, on a daily basis, on the lifestyle, mood and opinion of millions of Internet users. Nonetheless, such algorithms lack transparency challenging researchers to improve their fairness and accountability. In this paper, we propose a model to capture the dynamics of contents over a timeline (also known as news feed). The input to our model is a fundamental quantity associated to timelines, which we show that can be easily parameterized using real world data: the arrival rate of posts of a given publisher followed by the user. Using real world Facebook traces from the latest elections in Italy, we validate the accuracy of the proposed model and use the model for conterfactual what-if analysis.