Papers by Peter Stefanov

    1 papers
    Predicting the Topical Stance and Political Leaning of Media using Tweets (2020.acl-main)

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    Challenge: Existing methods for determining stances of media outlets and influential people are expensive.
    Approach: They propose a method that uses unsupervised learning to ascertain the stance of Twitter users with respect to a polarizing topic by leveraging their retweet behavior.
    Outcome: The proposed method achieves 82.6% accuracy compared to gold labels from the Media Bias/Fact Check website .

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