Margaret E. Roberts

Publications43
h-index23
Citations5,930
Highly Influential Citations475
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Structural Topic Models for Open‐Ended Survey Responses
TLDR
The structural topic model makes analyzing open-ended responses easier, more revealing, and capable of being used to estimate treatment effects, and is illustrated with analysis of text from surveys and experiments.
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stm: An R Package for Structural Topic Models
TLDR
This paper demonstrates how to use the R package stm for structural topic modeling, which allows researchers to flexibly estimate a topic model that includes document-level metadata.
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How Censorship in China Allows Government Criticism But Silences Collective Expression
We offer the first large scale, multiple source analysis of the outcome of what may be the most extensive effort to selectively censor human expression ever implemented. To do this, we have devised a…
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A Model of Text for Experimentation in the Social Sciences
TLDR
A hierarchical mixed membership model for analyzing topical content of documents, in which mixing weights are parameterized by observed covariates is posit, enabling researchers to introduce elements of the experimental design that informed document collection into the model, within a generally applicable framework.
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How the Chinese Government Fabricates Social Media Posts for Strategic Distraction, Not Engaged Argument
The Chinese government has long been suspected of hiring as many as 2 million people to surreptitiously insert huge numbers of pseudonymous and other deceptive writings into the stream of real social…
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Censored: Distraction and Diversion Inside China's Great Firewall
Reverse-engineering censorship in China: Randomized experimentation and participant observation
TLDR
It appears that criticism on the web, which was thought to be censored, is used by Chinese leaders to determine which officials are not doing their job of mollifying the people and need to be replaced.
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Computer-Assisted Text Analysis for Comparative Politics
TLDR
Practical issues that arise in the processing, management, translation, and analysis of textual data are discussed with a particular focus on how procedures differ across languages.
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The structural topic model and applied social science
TLDR
The Structural Topic Model (STM), a general way to incorporate corpus structure or document metadata into the standard topic model, is developed which accommodates corpus structure through document-level covariates affecting topical prevalence and/or topical content.
Navigating the Local Modes of Big Data: The Case of Topic Models
TLDR
This chapter analyzes a corpus of 13,246 posts that were written for six political blogs during the course of the 2008 U.S. presidential election, focusing on a particular variant of LDA, the structural topic model (STM) (Roberts et al., 2014), which provides a framework to relate the corpus structure the authors do have with the inferred topical structure of the model.
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