Prof. Miriam Fernandez recently attended the prestigious WEBSCI’24, the 16th ACM Web Science Conference, where she presented her latest research paper titled “Analysing the Effect of Recommendation Algorithms on the Spread of Misinformation.”

In the digital age, recommendation algorithms play a crucial role in shaping the information we see online. These algorithms are designed to suggest content that aligns with our interests, but they are often blamed for spreading misinformation. It is however still unclear which particular recommendation approaches are more prone to suggest misinforming items, or which internal parameters of the algorithms could be influencing more on their misinformation propagation capacity.

Prof.Fernandez research aims to fill these knowledge gaps by analysing how some of the most popular recommendation algorithms affect the spread of misinformation. Her work delves into the mechanics of these algorithms to identify which approaches are more prone to spreading false information and what internal parameters might influence their behaviour.

Based on her analysis and a comprehensive review of existing research, Prof. Fernandez presented a set of guidelines to help improve recommendation algorithms. These guidelines are designed to reduce the spread of misinformation by adjusting the algorithms to be more discerning in their content suggestions.

The conference, organised this year by the University of Stuttgart is a significant event that brings together experts from various fields to discuss how the web influences and is influenced by society, technology, and culture.

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Access publication in Open Research Online: Analysing the Effect of Recommendation Algorithms on the Spread of Misinformation.