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LLM pipeline extracts political claims from social media at scale

Researchers have developed a pipeline utilizing large language models (LLMs) to extract and categorize claims from extensive social media datasets. This method was applied to Twitter data concerning the 2020 US presidential election and the 2022 FIFA World Cup. The pipeline's effectiveness was rigorously assessed through precision and recall measurements against manually annotated samples, ablation studies, and qualitative error analysis, highlighting its utility for computational social science research. AI

IMPACT This methodology could enhance the analysis of political discourse and polarization on social media platforms.

RANK_REASON The item is a research paper detailing a new methodology for claims extraction. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

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LLM pipeline extracts political claims from social media at scale

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The item is a research paper detailing a new methodology for claims extraction. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Sandrine Chausson, Bj\"orn Ross ·

    Inductive Claims Extraction at Scale

    arXiv:2610.05275v2 Announce Type: replace Abstract: A large part of political discourse on social media is built and expressed at a level of claims: i.e. declarative, typically single-clause statements, which convey a particular interpretation of reality and can range from factua…