{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/challenges-of-using-text-classifiers-for","title":"Challenges of Using Text Classifiers for Causal Inference","arxiv_id":"1810.00956","date":"2018-10-01","proceeding":"EMNLP 2018 10","authors":["Zach Wood-Doughty","Ilya Shpitser","Mark Dredze"],"abstract":"Causal understanding is essential for many kinds of decision-making, but\ncausal inference from observational data has typically only been applied to\nstructured, low-dimensional datasets. While text classifiers produce\nlow-dimensional outputs, their use in causal inference has not previously been\nstudied. To facilitate causal analyses based on language data, we consider the\nrole that text classifiers can play in causal inference through established\nmodeling mechanisms from the causality literature on missing data and\nmeasurement error. We demonstrate how to conduct causal analyses using text\nclassifiers on simulated and Yelp data, and discuss the opportunities and\nchallenges of future work that uses text data in causal inference.","url_abs":"http://arxiv.org/abs/1810.00956v1","url_pdf":"http://arxiv.org/pdf/1810.00956v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"challenges-of-using-text-classifiers-for","repo_url":"https://github.com/zachwooddoughty/emnlp2018-causal","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"causal-inference","task_name":"Causal Inference"},{"task_slug":"decision-making","task_name":"Decision Making"}],"methods":[{"method_slug":"causal-inference","method_name":"Causal inference"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1810.00956","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1810.00956"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. 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