Papers by Tony Mullen

1 papers
Exploiting contextual information to improve stance detection in informal political discourse with LLMs (2025.acl-srw)

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Challenge: Political stance detection is an increasingly relevant part of analyzing the flow of ideas in online environments where discourse is informal and implicitly expressed.
Approach: They evaluate large language models for political stance detection in informal online discourse by analyzing user profiles derived from historical posts.
Outcome: The proposed model improves accuracy by up to 74% on a political forum dataset.

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