Some Reflections on Drawing Causal Inference using Textual Data: Parallels Between Human Subjects and Organized Texts

Bo Zhang, Jiayao Zhang

Keywords: causal inference, constructivism, natural language processing, potential outcomes framework, pretreatment variables

TL;DR: We discuss causal concepts/principles and identify ambiguities/inconsistencies when conducting inference using texts as study units; we then present strategies to better frame causal queries.

Abstract: We examine the role of textual data as study units when conducting causal inference by drawing parallels between human subjects and organized texts. We elaborate on key causal concepts and principles, and expose some ambiguity and sometimes fallacies. To facilitate better framing a causal query, we discuss two strategies: (i) shifting from immutable traits to perceptions of them, and (ii) shifting from some abstract concept/property to its constituent parts, i.e., a constructivist perspective of an abstract concept. We hope this article would raise the awareness of the importance of articulating and clarifying fundamental concepts before delving into developing methodologies when drawing causal inference using textual data.