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Feedback loops in the interplay of manual news sharing and algorithmic recommendations

PhD Student: Zilin Lin MSc

How does news dissemination work on social media? To answer this question, this project focuses on the news consumers perspective and investigates the complex interplay of manual news sharing and algorithmic recommendations with an innovative methodological toolbox.

Two approaches (i.e., data donations and sock puppets) will first be applied to collect evidence of real-world sharing scenarios and algorithmic recommendations, after which agent-based modelling will be used to simulate the interaction between human behaviors and algorithmic configurations. The model obtained from this simulation will then be empirically tested using online field experiments. Taken together, this project will offer insights into the relationship between manual and algorithmic feedback loops.

Z. (Zilin) Lin

PhD Student

Dr. D.C. (Damian) Trilling

Supervisor

S.A.M. (Susan) Vermeer MSc

Supervisor