Justin Grimmer

Publications81
h-index19
Citations3,378
Highly Influential Citations236
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Text as Data: The Promise and Pitfalls of Automatic Content Analysis Methods for Political Texts
Politics and political conflict often occur in the written and spoken word. Scholars have long recognized this, but the massive costs of analyzing even moderately sized collections of texts have… Expand
A Bayesian Hierarchical Topic Model for Political Texts: Measuring Expressed Agendas in Senate Press Releases
TLDR
We introduce a statistical model to measure the priorities political actors articulate in texts, which I apply to measure how legislators explain their work to constituents. Expand
Are Close Elections Random
Elections with small margins of victory represent an important form of democratic competition and, increasingly, an opportunity for causal inference. When scholars use close elections for examining… Expand
Representational Style in Congress: What Legislators Say and Why It Matters
1. Representation inside and outside Congress 2. Representation and evaluation on the senator's terms 3. Measuring presentational styles with Senate press releases 4. Measuring presentational styles… Expand
General purpose computer-assisted clustering and conceptualization
  • Justin Grimmer, G. King
  • Computer Science, Medicine
  • Proceedings of the National Academy of Sciences
  • 3 February 2011
TLDR
We develop a computer-assisted method for the discovery of insightful conceptualizations, in the form of clusterings (i.e., partitions) of input objects. Expand
Estimating Heterogeneous Treatment Effects and the Effects of Heterogeneous Treatments with Ensemble Methods
TLDR
We show how an ensemble of methods—weighted averages of estimates from individual models increasingly used in machine learning—accurately measure heterogeneous treatment effects can contribute to accurate estimation of heterogeneous effects. Expand
TopicCheck: Interactive Alignment for Assessing Topic Model Stability
TLDR
We introduce TopicCheck, an interactive tool for assessing the stability of topic models for automated content analysis. Expand
How Words and Money Cultivate a Personal Vote: The Effect of Legislator Credit Claiming on Constituent Credit Allocation
the district—affect how constituents allocate credit. Legislators use credit claiming messages to influence the expenditures they receive credit for and to affect how closely they are associated with… Expand
How to Make Causal Inferences Using Texts
TLDR
We introduce a conceptual framework for making causal inferences with discovered measures as a treatment or outcome and apply it to estimate causal effects. Expand
Appropriators not Position Takers: The Distorting Effects of Electoral Incentives on Congressional Representation
Congressional districts create two levels of representation. Studies of representation focus on a disaggregated level: the electoral connection between representatives and constituents. But there is… Expand
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