Forecasting elections results via the voter model with stubborn nodes

Autor: Antoine Vendeville, Benjamin Guedj, Shi Zhou

Publikováno v: Applied Network Science, Vol 6, Iss 1, Pp 1-13 (2021)

Abstract In this paper we propose a novel method to forecast the result of elections using only official results of previous ones. It is based on the voter model with stubborn nodes and uses theoretical results developed in a previous work of ours. W

Externí odkaz: https://doaj.org/article/46207fef60c147c5ad7a767869898a25

Opening up echo chambers via optimal content recommendation

Autor: Antoine Vendeville, Anastasios Giovanidis, Effrosyni Papanastasiou, Benjamin Guedj

Publikováno v: Proc. of the 11th International Conference on Complex Networks and their Applications
The 11th International Conference on Complex Networks and their Applications (CNA'22)
The 11th International Conference on Complex Networks and their Applications (CNA'22), Nov 2022, Palermo, Italy
HAL

International audience; Online social platforms have become central in the political debate. In this context, the existence of echo chambers is a problem of primary relevance. These clusters of like-minded individuals tend to reinforce prior beliefs,

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bfaab82091a7044a1fb5974588312cf7
https://hal.science/hal-03691800

Forecasting elections results via the voter model with stubborn nodes

Autor: Shi Zhou, Benjamin Guedj, Antoine Vendeville

Publikováno v: Applied Network Science
Applied Network Science, 2021
Applied Network Science, Springer, 2021
Applied Network Science, Vol 6, Iss 1, Pp 1-13 (2021)

15 pages; International audience; We explore a method to influence or even control the diversity of opinions within a polarised social group. We leverage the voter model in which users hold binary opinions and repeatedly update their beliefs based on

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7228c8131ae1184d5a1e6b6c5ff3cdba
https://inria.hal.science/hal-02946434v2/document

Performance Analysis of Online Social Platforms

Autor: Bruno Baynat, Antoine Vendeville, Anastasios Giovanidis

Publikováno v: IEEE International Conference on Computer Communications (INFOCOM) 2019
IEEE International Conference on Computer Communications (INFOCOM) 2019, IEEE, Apr 2019, PARIS, France. ⟨10.1109/INFOCOM.2019.8737539⟩
INFOCOM

We introduce an original mathematical model to analyze the diffusion of posts within a generic online social platform. Each user of such a platform has his own Wall and Newsfeed, as well as his own self-posting and re-posting activity. As a main resu

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2cf092add334179fe6260e0f52b71f50
https://hal.archives-ouvertes.fr/hal-01941296