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stm : R Package for Structural Topic Models

• Margaret E. Roberts, Brandon M. Stewart, Dustin Tingley
• 2014

This vignette demonstrates how to use the Structural Topic Model stm R package. The Structural Topic Model allows researchers to flexibly estimate a topic model that includes document-level… (More)

Reverse-engineering censorship in China: Randomized experimentation and participant observation

• Graham King, Jennifer Pan, Margaret E. Roberts
• Science
• 2014

Existing research on the extensive Chinese censorship organization uses observational methods with well-known limitations. We conducted the first large-scale experimental study of censorship by… (More)

The Structural Topic Model and Applied Social Science ∗

• Margaret E. Roberts, Brandon M. Stewart
• 2013

We develop the Structural Topic Model which provides a general way to incorporate corpus structure or document metadata into the standard topic model. Document-level covariates enter the model… (More)

Navigating the Local Modes of Big Data: The Case of Topic Models

• Margaret E. Roberts, Brandon M. Stewart, Dustin Tingley
• Computational Social Science
• 2016

How the Chinese Government Fabricates Social Media Posts for Strategic Distraction , not Engaged Argument ∗ †

• Graham King, Jennifer Pan, Margaret E. Roberts
• 2016

The Chinese government has long been suspected of hiring as many as 2,000,000 people to surreptitiously insert huge numbers of pseudonymous and other deceptive writings into the stream of real social… (More)

Matching Methods for High-Dimensional Data with Applications to Text ∗

• Margaret E. Roberts, Brandon M. Stewart, Richard O. Nielsen
• 2015

Matching is a technique for preprocessing observational data to facilitate causal inference and reduce model dependence by ensuring that treated and control units are balanced along pre-treatment… (More)

Computer-Assisted Keyword and Document Set Discovery from Unstructured Text

• Gary King, Patrick Lam, Margaret E. Roberts
• 2014

The (unheralded) first step in many applications of automated text analysis involves selecting keywords to choose documents from a large text corpus for further study. Although all substantive… (More)

TopicCheck: Interactive Alignment for Assessing Topic Model Stability

• Jason Chuang, Margaret E. Roberts, +4 authors Jeffrey Heer
• HLT-NAACL
• 2015

Content analysis, a widely-applied social science research method, is increasingly being supplemented by topic modeling. However, while the discourse on content analysis centers heavily on… (More)

How to Make Causal Inferences Using Texts

• Naoki Egami, Christian J. Fong, Justin Grimmer, Margaret E. Roberts, Brandon M. Stewart
• ArXiv
• 2017

New text as data techniques offer a great promise: the ability to inductively discover measures that are useful for testing social science theories of interest from large collections of text. We… (More)

Adjusting for Confounding with Text Matching ∗

• Margaret E. Roberts, Brandon M. Stewart, Richard A. Nielsen
• 2018

We identify situations in which conditioning on text can address confounding in observational studies. We argue that a matching approach is particularly well-suited to this task, but existing… (More)

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