A Design-based Solution for Causal Inference with Text: Can a Language Model Be Too Large?
文本因果推断的设计式方案：语言模型会不会过大？
Many social science questions ask how linguistic properties causally affect an audience's attitudes and behaviors. Because text properties are often interlinked (e.g., angry reviews use profane language), we must control for possible latent confounding to isolate causal effects. Recent literature proposes adapting large language models (LLMs) to learn latent representations of text that successfully predict both treatment and the outcome. However, because the treatment is a…