Papers by Naama Rivlin-Angert

2 papers
The Enemy from Within: A Study of Political Delegitimization Discourse in Israeli Political Speech (2025.emnlp-main)

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Challenge: a new computational model for political delegitimization discourse is proposed for analysis of democratic discourse . we identify the importance of PDD as a powerful tool in political competition .
Approach: They propose a computational classification pipeline for political delegitimization discourse . they annotate a Hebrew-language corpus of 10,410 sentences from parliamentary speeches, facebook posts and leading news outlets .
Outcome: The proposed model achieves an F1 of 0.74 for binary detection and a macro-F1 of 0.6 for classification of delegitimization characteristics.
HebID: Detecting Social Identities in Hebrew-language Political Text (2025.findings-emnlp)

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Challenge: Existing NLP datasets focus on coarse-grained identity categories . existing datasets are mostly English-centric and focus on fine-grain categories based on cultural contexts.
Approach: They introduce the first multilabel Hebrew corpus for social identity detection . they use Hebrew-tuned encoders alongside 2B-9B-parameter decoders .
Outcome: The proposed classifier is based on a national public survey and uses Hebrew-tuned encoders to analyze political discourse and political speeches.

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