mlsanityData to 14 Oct 2026

Polarized Online Discourse on Abortion: Frames and Hostile Expressions among Liberals and Conservatives

arXiv 2311.16831 ↗First posted 28 Nov 2023cs.CY cs.CLcited by 4

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Abstract (arXiv)

Abortion has been one of the most divisive issues in the United States. Yet, missing is comprehensive longitudinal evidence on how political divides on abortion are reflected in public discourse over time, on a national scale, and in response to key events before and after the overturn of Roe v Wade. We analyze a corpus of over 3.5M tweets related to abortion over the span of one year (January 2022 to January 2023) from over 1.1M users. We estimate users' ideology and rely on state-of-the-art transformer-based classifiers to identify expressions of hostility and extract five prominent frames surrounding abortion. We use those data to examine (a) how prevalent were expressions of hostility (i.e., anger, toxic speech, insults, obscenities, and hate speech), (b) what frames liberals and conservatives used to articulate their positions on abortion, and (c) the prevalence of hostile expressions in liberals and conservative discussions of these frames. We show that liberals and conservatives largely mirrored each other's use of hostile expressions: as liberals used more hostile rhetoric, so did conservatives, especially in response to key events. In addition, the two groups used distinct frames and discussed them in vastly distinct contexts, suggesting that liberals and conservatives have differing perspectives on abortion. Lastly, frames favored by one side provoked hostile reactions from the other: liberals use more hostile expressions when addressing religion, fetal personhood, and exceptions to abortion bans, whereas conservatives use more hostile language when addressing bodily autonomy and women's health. This signals disrespect and derogation, which may further preclude understanding and exacerbate polarization.

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 5 of its 79 references that are in the map. First posted on arXiv 28 Nov 2023.

Builds on

5 of 79 references.

References · 5

  1. 2020TweetEval: Unified Benchmark and Comparative Evaluation for Tweet Classificationcited by 417
  2. 2021SpanEmo: Casting Multi-label Emotion Classification as Span-predictioncited by 37
  3. 2023#RoeOverturned: Twitter Dataset on the Abortion Rights Controversycited by 14
  4. 2023Pandemic Culture Wars: Partisan Differences in the Moral Language of COVID-19 Discussionscited by 6
  5. 2020Weak ties strengthen anger contagion in social mediacited by 2

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 2; 2025: 1; 2026: 1.

4 papers.