Ideological congruence in the digital public sphere: linking corporate political donations to online audience composition on X (Twitter)

Abstract In an era of deepening political polarization, corporate political activism has emerged as a critical nexus of consumer-brand interaction. This study investigates the alignment between U.S. corporations’ offline political donations and the ideological composition of their online audiences on the X (formerly Twitter) platform. While existing research often relies on surveys, extensive empirical evidence from real-world social media remains limited. To address this gap, this research employs a novel computational approach, analyzing a large-scale X dataset to construct a political retweet network. Audience ideology is inferred using a validated community detection method. The analysis finds a robust association between the partisan direction of corporate donations and the ideological makeup of their X audience, a relationship that persists after controlling for firm-level factors. Furthermore, ideological misalignment is associated with a meaningful increase in negative online engagement. This study provides evidence consistent with social identity theory in consumer-brand dynamics and demonstrates the utility of computational methods for linking offline political actions to online social structures, offering crucial insights for navigating reputational risk in a polarized digital landscape.

Authors

Institutions

Publication Details

Journal
Journal of Computational Social Science
Published
2026-05-21
DOI
https://doi.org/10.1007/s42001-026-00477-0
Primary Topic
Social Media and Politics
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Ideological congruence in the digital public sphere: linking corporate political donations to online audience composition on X (Twitter)

Jinghui Chen, Takayuki Mizuno
Journal of Computational Social Science
Social Media and Politics
article

Ideological congruence in the digital public sphere: linking corporate political donations to online audience composition on X (Twitter)

Jinghui Chen, Takayuki Mizuno
article en

Abstract

Abstract In an era of deepening political polarization, corporate political activism has emerged as a critical nexus of consumer-brand interaction. This study investigates the alignment between U.S. corporations’ offline political donations and the ideological composition of their online audiences on the X (formerly Twitter) platform. While existing research often relies on surveys, extensive empirical evidence from real-world social media remains limited. To address this gap, this research employs a novel computational approach, analyzing a large-scale X dataset to construct a political retweet network. Audience ideology is inferred using a validated community detection method. The analysis finds a robust association between the partisan direction of corporate donations and the ideological makeup of their X audience, a relationship that persists after controlling for firm-level factors. Furthermore, ideological misalignment is associated with a meaningful increase in negative online engagement. This study provides evidence consistent with social identity theory in consumer-brand dynamics and demonstrates the utility of computational methods for linking offline political actions to online social structures, offering crucial insights for navigating reputational risk in a polarized digital landscape.

Journal of Computational Social ScienceVol. 9(3)
National Institute of Informatics (JP), The Graduate University for Advanced Studies, SOKENDAI (JP)
Japan Society for the Promotion of Science
Openalex Percentile: Top 5%
Social Media and Politics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.