American Journal of Political Science· 2014Q1
Structural Topic Models for Open‐Ended Survey Responses
- 1,949citations
- Q1SCImago
- 2014year
Short summary
This paper introduces the Structural Topic Model (STM), a semi-automated machine learning approach for analyzing open-ended survey responses, offering an alternative to traditional human coding.
AI-generated from the title and abstract; the full text is not read.
Key points
- Introduces the Structural Topic Model (STM) for analyzing open-ended survey text.
- STM is a semi-automated, machine learning-based approach.
- Unique feature: incorporates document metadata (e.g., author gender, political affiliation) into topic analysis.
- Enables easier, more revealing analysis and estimation of treatment effects.
AI-generated from the title and abstract; the full text is not read.
Abstract
Collection and especially analysis of open‐ended survey responses are relatively rare in the discipline and when conducted are almost exclusively done through human coding. We present an alternative, semiautomated approach, the structural topic model (STM) (Roberts, Stewart, and Airoldi 2013; Roberts et al. 2013), that draws on recent developments in machine learning based analysis of textual data. A crucial contribution of the method is that it incorporates information about the document, such as the author's gender, political affiliation, and treatment assignment (if an experimental study). This article focuses on how the STM is helpful for survey researchers and experimentalists. The STM makes analyzing open‐ended responses easier, more revealing, and capable of being used to estimate treatment effects. We illustrate these innovations with analysis of text from surveys and experiments.
The authors' abstract, as published at the source. American Journal of Political Science, 2014 · DOI ↗
Continue with a free account
Ask the paper: 3 free questions a day about this paper; save it, get its citation, new summaries every day for your field. Takeaways are Premium.
Continue free on the webSign in with Google or Apple; no card needed. You come back to this paper.
On your phone:
Field: General Social Sciences
General Social SciencesSocial Sciences