Theory-Grounded Computational Text Analysis
Arya D. McCarthy, Giovanna Maria Dora Dore
Abstract
In this position paper, we argue that computational text analysis lacks and requires organizing principles. A broad space separates its two constituent disciplines—natural language processing and social science—which has to date been sidestepped rather than filled by applying increasingly complex computational models to problems in social science research. We contrast descriptive and integrative findings, and our review of approximately 60 papers on computational text analysis reveals that those from *ACL venues are typically descriptive. The lack of theory began at the area’s inception and has over the decades, grown more important and challenging. A return to theoretically grounded research questions will propel the area from both theoretical and methodological points of view.
BibTeX
@inproceedings{mccarthy-dore-2023-theory,
title = "Theory-Grounded Computational Text Analysis",
author = "McCarthy, Arya D. and
Dore, Giovanna Maria Dora",
editor = "Rogers, Anna and
Boyd-Graber, Jordan and
Okazaki, Naoaki",
booktitle = "Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)",
month = jul,
year = "2023",
address = "Toronto, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.acl-short.136/",
doi = "10.18653/v1/2023.acl-short.136",
pages = "1586--1594"
}