Yasmeen Abdrabou (University of the Bundeswehr Munich), Elisaveta Karypidou (LMU Munich), Florian Alt (University of the Bundeswehr Munich), Mariam Hassib (University of the Bundeswehr Munich)

We propose an approach to identify users’ exposure to fake news from users’ gaze and mouse movement behavior. Our approach is meant as an enabler for interventions that make users aware of engaging with fake news while not being consciously aware of this. Our work is motivated by the rapid spread of fake news on the web (in particular, social media) and the difficulty and effort required to identify fake content, either technically or by means of a human fact checker. To this end, we set out with conducting a remote online study (N = 54) in which participants were exposed to real and fake social media posts while their mouse and gaze movements were recorded. We identify the most predictive gaze and mouse movement features and show that fake news can be predicted with 68.4% accuracy from users’ gaze and mouse movement behavior. Our work is complemented by discussing the implications of using behavioral features for mitigating the spread of fake news on social media.

View More Papers

Vision: Comparison of AI-assisted Policy Development Between Professionals and...

Rishika Thorat (Purdue University), Tatiana Ringenberg (Purdue University)

Read More

Work in Progress: A Comparative Long-Term Study of Fallback...

Philipp Markert, Maximilian Golla (Ruhr University Bochum); Elizabeth Stobert (National Research Council of Canada); Markus Dürmuth (Ruhr University Bochum)

Read More

“So I Sold My Soul“: Effects of Dark Patterns...

Oksana Kulyk (ITU Copenhagen), Willard Rafnsson (IT University of Copenhagen), Ida Marie Borberg, Rene Hougard Pedersen

Read More

Location Spoofing Attacks on Autonomous Fleets

Jinghan Yang, Andew Estornell, Yevgeniy Vorobeychik (Washington University in St. Louis)

Read More