Does Topic Sentiment Cause Perceived Ideology? Comparing Human and LLM Annotations in Political News Articles
We ask whether topic sentiment has a causal effect on perceived political ideology, and whether the answer depends on who assigns the ideology label. Using articles from AllSides, paired with shared sentiment annotations from Llama-3.3-70b-versatile, we compare ideology labels from expert human annotators, GPT-4o-mini (baseline and finetuned), and Llama-3.3-70B. We apply Double Machine Learning (DML) and mediation analysis across all four annotation paradigms. Zero-shot LLMs regularly inflate effect sizes relative to human annotations, while fine-tuning often attenuates them back toward the human scale. Our results have implications for the use of LLM annotations as silver labels and as p...
| Authors | Upasana Chatterjee |
|---|---|
| Primary category | cs.CL |
| Published | 4 June 2026 |
| Last updated at source | 14 July 2026 |
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