About me
I am a Post-doctoral researcher at the médialab Sciences Po in Paris. I work on the AI-Political Machines project under the supervision of Pedro Ramaciotti Morales.
At the intersection of theoretical models and empirical analyses, my research focuses on the structure of online political and informational landscapes. Recently, I have been working on the public release and the analysis of large X databases, focusing on the multidimensional structure of the users’ political opinions. I am also greatly interested in the validation of opinion dynamics models with empirical data, and in the study of signed networks. In general, I strive to conduct research to better understand the impact of social media on our societies.
Previously, I was a PhD student in the Computer Science department of University College London, where I studied the echo chamber effect in social media and proposed methods to mitigate it. I was part of the Centre for Doctoral Training in Cybersecurity. My research project was supervised by Benjamin Guedj and Shi Zhou.
I am also affiliated with the Paris Institute of Complex Systems and the Learning Planet Institute.
Data
We just released a public database with measurements of multidimensional political opinions, activity and popularity for almost a million X users, including politicians and media outlets.
Latest publication
Voter model can accurately predict individual opinions in online populations
- A. Vendeville. Voter model can accurately predict individual opinions in online populations. Physical Review E, 111, 064310. Preprint on arXiv, HAL. Featured in Physics Magazine.
In this paper, I show that the Voter Model can predict individual opinions in a large, heterogeneous online population. I study a retweet network collected during the 2017 French presidential elections where accounts of political entities are fixed as reference points. I show that in its equilibrium state, the Voter Model correctly identifies ground-truth opinions of more than 92% of the users.
