Papers by David Jensen

    1 papers
    Text and Causal Inference: A Review of Using Text to Remove Confounding from Causal Estimates (2020.acl-main)

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    Challenge: Unmeasured or latent confounders can bias causal estimates and this has motivated interest in measuring potential confounder from observed text.
    Approach: They propose to use text to measure potential confounders in a way that allows for a rich measurement of multiple confounder variables.
    Outcome: The proposed method is based on an individual’s entire history of social media posts or the content of a news article.

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