English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

We develop a broadly applicable class of coevolving latent space network withattractors (CLSNA) models, where nodes represent individual social actorsassumed to lie in an unknown latent space, edges represent the presence of aspecified interaction between actors, and attractors are added in the latentlevel to capture the notion of attractive and repulsive forces. We apply theCLSNA models to understand the dynamics of partisan polarization on socialmedia, where we expect Republicans and Democrats to increasingly interact withtheir own party and disengage with the opposing party. Using longitudinalsocial networks from the social media platforms Twitter and Reddit, weinvestigate the relative contributions of positive (attractive) and negative(repulsive) forces among political elites and the public, respectively. Ourgoals are to disentangle the positive and negative forces within and betweenparties and explore if and how they change over time. Our analysis confirms theexistence of partisan polarization in social media interactions among bothpolitical elites and the public. Moreover, while positive partisanship is thedriving force of interactions across the full periods of study for both thepublic and Democratic elites, negative partisanship has come to dominateRepublican elites' interactions since the run-up to the 2016 presidentialelection.

Disentangling positive and negative partisanship in social media interactions using a coevolving latent space network with attractors model