Evidence map›Paper›PMID 41406133›Full record

ArticlePLOS global public health2025

How do mass shootings shape the social media discourse on guns in the US Congress? Causal discovery and topic modeling.

Dmytro Bukhanevych, Rayan Succar, Maurizio Porfiri

Abstract read
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Article in PLOS global public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

3 authors.

Dmytro BukhanevychCenter for Urban Science and Progress, Tandon School of Engineering, New York University, Brooklyn, New York, United States of America.ORCID https://orcid.org/0009-0004-5157-8635
Rayan SuccarCenter for Urban Science and Progress, Tandon School of Engineering, New York University, Brooklyn, New York, United States of America.
Maurizio PorfiriCenter for Urban Science and Progress, Tandon School of Engineering, New York University, Brooklyn, New York, United States of America.ORCID https://orcid.org/0000-0002-1480-3539

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Social media platforms have become a key tool for politicians to signal their policy positions and communicate about issues that are salient to them and their constituency. One such issue is gun violence. Grounded in framing and issue-attention cycle theories, this paper analyzes the response of members of the United States (US) Congress to mass shootings on social media. We analyzed 785,881 gun-related tweets from members of the 117th US Congress on X (formerly Twitter) between January 2021 and January 2023. We used logistic regression to model the main effects, implemented the PCMCI+ algorithm for causal discovery, and applied latent Dirichlet allocation topic modeling to evaluate the substantive differences between gun-related tweets from the two parties. Higher fatality counts were positively correlated with the probability of gun-related tweets by Congress members (OR=1.13, 95% CI=[1.12, 1.15], p < 0.001). A causal link was detected between mass shootings and subsequent legislators' activity on X (ρ=0.122, p=0.001). Democrats were more likely to tweet about guns following mass shootings than Republicans (OR=3.60, 95% CI=[3.03, 4.28], p < 0.001), with qualitative differences in tweet substance between parties (community, families, victims, and mass shootings themselves are recurrent topics for Democrats, while Second Amendment rights and crime are frequent for Republicans). The paper suggests that while mass shootings elevate the level of discussion on guns in Congress, they trigger different reactions depending on party affiliation. Congress members tend to focus on topics aligned with party issues, likely reducing the opportunity for policy-making alignment.

Identifiers

PMID41406133
PMCPMC12711034

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