causaltext/causal-text-papers
Curated research at the intersection of causal inference and natural language processing.
This project is a curated collection of research papers and associated codebases that explore the relationship between causal inference and natural language processing. It helps researchers, social scientists, and data scientists understand how text data can be used to estimate causal effects, whether text is a cause, an effect, or an influencing factor. It provides structured insights into existing methodologies and applications.
814 stars. No commits in the last 6 months.
Use this if you are a researcher or practitioner in fields like social sciences, marketing, or psychology, and you need to understand how linguistic properties or textual content can influence outcomes, or how to account for text in causal analysis.
Not ideal if you are looking for an out-of-the-box software tool to directly apply causal inference to your text data without engaging with academic literature or implementing research methods.
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Feb 01, 2024
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