Evidence map›Paper›PMID 42594118›Full record

ArticlePloS one2026

Disciplining the digital public: Platform mechanisms and the dynamics of emotional polarization.

Changrong Lu, Dan Qin, Jiali Huang, Bing Pang

Abstract read
In one paragraph

Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Changrong LuNagoya University of Commerce and Business, Nisshin, Aichi, Japan.ORCID https://orcid.org/0000-0002-2351-3672
Dan QinNagoya University of Commerce and Business, Nisshin, Aichi, Japan.
Jiali HuangShanghai Institutes for International Studies, Shanghai, China.
Bing PangGraduate School of Asia-Pacific Studies, Waseda University, Tokyo, Japan.ORCID https://orcid.org/0009-0004-1158-8329

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Digital platforms increasingly mediate political communication and public opinion formation, raising urgent questions about how Bigtech firms are associated with behavioral norm formation and affective dynamics. This study develops the concept of platform disciplinary mechanisms to examine how interface design, algorithmic recommendation, and interaction feedback correspond to behavioral standardization, cognitive dependency, and emotionally structured group differentiation across online communities. Using a platform-end user-community framework, we investigate whether technological conditions associated with platform governance correspond to systematic changes in emotional polarization within the platform-mediated information environment. We conduct a time-series analysis linking a daily emotional polarization indicator derived from aggregated news sentiment (GDELT) to technology-category intensity measures extracted from Bigtech research outputs indexed in the Web of Science. Because the polarization indicator is based on news sentiment rather than user traces, it captures emotional polarization in the information environment rather than individual psychological states. Treating 2020 as a theory-informed analytic breakpoint, we find that emotional polarization becomes more persistent after 2020 and is more strongly associated with higher levels of technological simplification and emotion-oriented interaction dynamics. These findings are consistent with the view that major platforms are linked to changes in public-opinion dynamics in platform-mediated environments characterized by affective governance. They also suggest that regulation should pay greater attention to structural mechanisms of behavioral normalization and affective manipulation beyond content moderation alone.

Indexed as

EmotionsPublic OpinionCommunicationDigital MediaHumansInternet

Identifiers

PMID42594118
PMCPMC13472384

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.