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Challenges of Using Text Classifiers for Causal Inference

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Figure

Figure 1: DAGs for causal inference without text data. Red variables are unobserved.A is a treatment, Y is an outcome, and C is a confounder.
Figure 3: DAGs for causal inference with text data. In the Yelp experiments we discuss, Ti influences Yand not the other way around.
Figure 5: Experimental results. Squared distance (y-axis, lower is better) of the estimated causal effectfor larger datasets) are 1.96 times standard error across 10 experiments
Figure 6: Experimental results with a vocabulary of size 53,197. Squared distance (y-axis, lower is better)of the estimated causal effect from τSC calculated from the full data with no missing data or measurementerror

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