Detecting patterns of coordinated news article dissemination

dc.contributor.author	Bodnar, Petro
dc.date.accessioned	2021-06-25T12:38:20Z
dc.date.available	2021-06-25T12:38:20Z
dc.date.issued	2021
dc.identifier.citation	Bodnar, Petro. Detecting patterns of coordinated news article dissemination / Petro Bodnar; Supervisor: Dmytro Karamshuk; Ukrainian Catholic University, Department of Computer Sciences. – Lviv : [s.n.], 2021. – 35 p.: ill.	uk
dc.identifier.uri	https://er.ucu.edu.ua/handle/1/2697
dc.language.iso	en	uk
dc.subject	detection of misinformation	uk
dc.subject	Multivariate Hawkes Processes	uk
dc.title	Detecting patterns of coordinated news article dissemination	uk
dc.type	Preprint	uk
dc.status	Публікується вперше	uk
dc.description.abstracten	This study aims at devising methods for detecting coordination among content spreaders at scale. We focus on methods which uncover the latent structure of the content dissemination networks from the time-series of publications. We identify the advantages of generative models, especially self-exiting stochastic processes, for modeling information cascades and detecting structural patterns in groups of events. We validate the most popular of these models – the Multivariate Hawkes processes – on a large dataset of news websites and achieve an improvement in comparison to simpler baselines, e.g., cosine similarity between time-series of publications.	uk