Papers by Andres Abeliuk

1 papers
Detecting Polarized Topics Using Partisanship-aware Contextualized Topic Embeddings (2021.findings-emnlp)

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Challenge: polarization of the news media has been blamed for fanning disagreement, controversy and even violence.
Approach: They propose a method to automatically detect polarized topics from partisan news sources by corpus-contextualized topic embedding a news corpus on a topic and using cosine distance to capture topical polarization.
Outcome: The proposed method captures topical polarization and shows it can retrieve the most polarized topics.

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