From Consensus to Split Decisions: ABC-Stratified Sentiment in Holocaust Oral Histories

• URL: http://arxiv.org/abs/2603.28913v1
• Date: Mon, 30 Mar 2026 18:44:22 GMT
• Title: From Consensus to Split Decisions: ABC-Stratified Sentiment in Holocaust Oral Histories
• Abstract summary: Polarity detection becomes substantially more challenging under domain shift.<n>This paper presents a corpus-scale diagnostic study of sentiment classifiers on long-form Holocaust oral histories.
• Score: 0.2538209532048867
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: Polarity detection becomes substantially more challenging under domain shift, particularly in heterogeneous, long-form narratives with complex discourse structure, such as Holocaust oral histories. This paper presents a corpus-scale diagnostic study of off-the-shelf sentiment classifiers on long-form Holocaust oral histories, using three pretrained transformer-based polarity classifiers on a corpus of 107,305 utterances and 579,013 sentences. After assembling model outputs, we introduce an agreement-based stability taxonomy (ABC) to stratify inter-model output stability. We report pairwise percent agreement, Cohen kappa, Fleiss kappa, and row-normalized confusion matrices to localize systematic disagreement. As an auxiliary descriptive signal, a T5-based emotion classifier is applied to stratified samples from each agreement stratum to compare emotion distributions across strata. The combination of multi-model label triangulation and the ABC taxonomy provides a cautious, operational framework for characterizing where and how sentiment models diverge in sensitive historical narratives. Inter-model agreement is low to moderate overall and is driven primarily by boundary decisions around neutrality.

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