Topic of the thesis: The performance of wisdom of crowds in fake news detection online. An analysis through a gamified online social experiment.

Abstract: The proposed project aims at focusing on an often overlooked aspect of fake news detection: the role of the public. We propose a gamified online social experiment to test the performance of the public in fake news detection and the factors influencing it. To test the impact of gamification, a non-gamified version of the experiment will also be submitted to another group of participants through the Amazon Mechanical Turk. These two group of participant will be then compared using sample matching in an “ex post facto” quasi experiment design. A comparison with a machine learning approach is then proposed. The aim of the comparison is to better understand the differences between these two approaches (human-based and machine-based) to the fake news detection task. Both approaches will be tested on the same manuallylabelled dataset of news articles.

Research interests: Fake news detection – Online social experiments – Gamification – Cognitive biases – Mass collaboration and wisdom of crowds – Computational social sciences.

Graduated from: University of Bologna.

Degrees obtained: BA in Political, Social and International Sciences – MA in Politics, Administration and Organization.

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