Polarization dynamics: a study of individuals shifting between political communities on social media

Abstract

Purpose-Led Publishing, find out more.Paper • The following article isOpen accessPolarization dynamics: a study of individuals shifting between political communities on social mediaFederico Albanese*, Esteban Feuerstein and Pablo BalenzuelaPublished 2 August 2024 • © 2024 The Author(s). Published by IOP Publishing LtdJournal of Physics: Complexity, Volume 5, Number 3Citation Federico Albanese et al 2024 J. Phys. Complex. 5 035008DOI 10.1088/2632-072X/ad679dDownloadArticle PDFAuthorsFiguresTablesReferencesOpen scienceDownload PDFArticle metrics496 Total downloadsArticle has an altmetric score of 3SubmitSubmit to this JournalShare this articleArticle informationAbstractIndividuals engaging on social media often tend to establish online communities where interactions predominantly occur among like-minded peers. While considerable efforts have been devoted to studying and delineating these communities, there has been limited attention directed towards individuals who diverge from these patterns. In this study, we examine the community structure of re-post networks within the context of a polarized political environment at two different times. We specifically identify individuals who consistently switch between opposing communities and analyze the key features that distinguish them. Our investigation focuses on two crucial aspects of these users: the topological properties of their interactions and the political bias in the content of their posts. Our analysis is based on a dataset comprising 2 million tweets related to US President Donald Trump, coupled with data from over 100 000 individual user accounts spanning the 2020 US presidential election year. Our findings indicate that individuals who switch communities exhibit disparities compared to those who remain within the same communities, both in terms of the topological aspects of their interaction patterns (pagerank, degree, betweenness centrality.) and in the sentiment bias of their content towards Donald Trump.