Structural Topic Models for Open-Ended Survey Responses
作者： Margaret E. Roberts , Brandon M. Stewart , Dustin Tingley , Christopher Lucas , Jetson Leder-Luis
DOI: 10.1111/AJPS.12103
关键词:
摘要: 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 …
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