Abstract
We introduce a procedure to examine a text-as-mediator problem from a novel randomized experiment that studied the effect of conversations on political polarization. In this randomized experiment, Americans from the Democratic and Republican parties were either randomly paired with one-another to have an anonymous conversation about politics or alternatively not assigned to a conversation — change in political polarization over time was measured for all participants. This paper analyzes the text of the conversations to identify potential mediators of depolarization and is faced with a unique challenge, necessitated by the primary research hypothesis, that individuals in the control condition do not have conversations and so lack observed text data. We highlight the importance of using domain knowledge to perform dimension reduction on the text data, and describe a procedure to characterize indirect effects via text when the text is only observed in one arm of the experiment.- Anthology ID:
- 2021.cinlp-1.5
- Volume:
- Proceedings of the First Workshop on Causal Inference and NLP
- Month:
- November
- Year:
- 2021
- Address:
- Punta Cana, Dominican Republic
- Editors:
- Amir Feder, Katherine Keith, Emaad Manzoor, Reid Pryzant, Dhanya Sridhar, Zach Wood-Doughty, Jacob Eisenstein, Justin Grimmer, Roi Reichart, Molly Roberts, Uri Shalit, Brandon Stewart, Victor Veitch, Diyi Yang
- Venue:
- CINLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 61–73
- Language:
- URL:
- https://aclanthology.org/2021.cinlp-1.5
- DOI:
- 10.18653/v1/2021.cinlp-1.5
- Cite (ACL):
- Graham Tierney and Alexander Volfovsky. 2021. Sensitivity Analysis for Causal Mediation through Text: an Application to Political Polarization. In Proceedings of the First Workshop on Causal Inference and NLP, pages 61–73, Punta Cana, Dominican Republic. Association for Computational Linguistics.
- Cite (Informal):
- Sensitivity Analysis for Causal Mediation through Text: an Application to Political Polarization (Tierney & Volfovsky, CINLP 2021)
- PDF:
- https://preview.aclanthology.org/emnlp-22-attachments/2021.cinlp-1.5.pdf