Mathematics
2 years ago

Text analysis revolutionizes causal inference, removing bias from non-experimental data.

arXiv (Cornell University)
Text and Causal Inference: A Review of Using Text to Remove Confounding from Causal Estimates
Katherine A. Keith, David Jensen, Brendan O’Connor

Paper Summary

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The article reviews how text can help figure out cause and effect relationships in social science research. By looking at things like social media posts or news articles, researchers can find hidden factors that might affect their results. Even though using text to adjust for these factors is getting more attention, there are still a lot of challenges to overcome.