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Title: Disentangling positive and negative partisanship in social media interactions using a coevolving latent space network with attractors model
Abstract We develop a broadly applicable class of coevolving latent space network with attractors (CLSNA) models, where nodes represent individual social actors assumed to lie in an unknown latent space, edges represent the presence of a specified interaction between actors, and attractors are added in the latent level to capture the notion of attractive and repulsive forces. We apply the CLSNA models to understand the dynamics of partisan polarization in US politics on social media, where we expect Republicans and Democrats to increasingly interact with their own party and disengage with the opposing party. Using longitudinal social networks from the social media platforms Twitter and Reddit, we quantify the relative contributions of positive (attractive) and negative (repulsive) forces among political elites and the public, respectively.  more » « less
Award ID(s):
2107856 2120115
PAR ID:
10427657
Author(s) / Creator(s):
; ; ; ; ;
Publisher / Repository:
Oxford University Press
Date Published:
Journal Name:
Journal of the Royal Statistical Society Series A: Statistics in Society
Volume:
186
Issue:
3
ISSN:
0964-1998
Format(s):
Medium: X Size: p. 463-480
Size(s):
p. 463-480
Sponsoring Org:
National Science Foundation
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