TY - GEN
T1 - Polarized, together
T2 - 13th International AAAI Conference on Web and Social Media, ICWSM 2019
AU - Joseph, Kenneth
AU - Swire-Thompson, Briony
AU - Masuga, Hannah
AU - Baum, Matthew A.
AU - Lazer, David
N1 - Publisher Copyright:
Copyright © 2019, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.
PY - 2019
Y1 - 2019
N2 - Using both survey- and platform-based measures of support, we study how polarization manifests for 4,313 of President Donald Trump’s tweets since he was inaugurated in 2017. We find high levels of polarization in response to Trump’s tweets. However, after controlling for mean differences, we surprisingly find a high degree of agreement across partisan lines across both survey and platform-based measures. This suggests that Republicans and Democrats, while disagreeing on an absolute level, tend to agree on the relative quality of Trump’s tweets. We assess potential reasons for this, for example, by studying how support changes in response to tweets containing positive versus negative language. We also explore how Democrats and Republicans respond to tweets containing insults of individuals with particular socio-demographics, finding that Republican support decreases when Republicans, relative to Democrats, are insulted, and Democrats respond negatively to insults of women and members of the media.
AB - Using both survey- and platform-based measures of support, we study how polarization manifests for 4,313 of President Donald Trump’s tweets since he was inaugurated in 2017. We find high levels of polarization in response to Trump’s tweets. However, after controlling for mean differences, we surprisingly find a high degree of agreement across partisan lines across both survey and platform-based measures. This suggests that Republicans and Democrats, while disagreeing on an absolute level, tend to agree on the relative quality of Trump’s tweets. We assess potential reasons for this, for example, by studying how support changes in response to tweets containing positive versus negative language. We also explore how Democrats and Republicans respond to tweets containing insults of individuals with particular socio-demographics, finding that Republican support decreases when Republicans, relative to Democrats, are insulted, and Democrats respond negatively to insults of women and members of the media.
UR - https://www.scopus.com/pages/publications/85070383692
M3 - Conference contribution
AN - SCOPUS:85070383692
SN - 9781577358060
T3 - Proceedings of the 13th International Conference on Web and Social Media, ICWSM 2019
SP - 290
EP - 301
BT - Proceedings of the 13th International AAAI Conference on Web and Social Media, ICWSM 2019
PB - Association for the Advancement of Artificial Intelligence
Y2 - 11 June 2019 through 14 June 2019
ER -