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New NLP research analyzes disagreement structures in emotion annotation

By PulseAugur Editorial · [1 sources] ·

A new paper published on arXiv explores the structure of disagreement in emotion annotation within natural language processing. The research analyzes multilabel annotations from three datasets, including Ernest Hemingway's "The Old Man and the Sea," to identify recurring patterns in how annotators disagree. The study found that disagreement can stem from overlapping emotion categories, differing interpretations of label boundaries, and variations in rating emotion intensity. The authors propose a vocabulary to better understand and describe these disagreement structures before they are aggregated or used in modeling. AI

IMPACT Provides a framework for understanding and modeling annotation disagreements, potentially improving the quality and reliability of NLP datasets.

RANK_REASON Academic paper on NLP methodology. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New NLP research analyzes disagreement structures in emotion annotation

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Academic paper on NLP methodology. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Emily \"Ohman, Anna Koufakou, Eugenia Diegoli ·

    The Structure of Disagreement in Emotion Annotation

    arXiv:2611.01539v1 Announce Type: new Abstract: Calculating inter-annotator agreement is an established practice in NLP, and disagreement-aware work increasingly retains the distribution of human judgments rather than reducing annotations to a single gold label. Keeping the distr…

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