Political Analysis

A Statistical Model of Bipartite Networks: Application to Cosponsorship in the United States Senate | Political Analysis | Cambridge Core A Statistical Model of Bipartite Networks: Application to Cosponsorship in the United States Senate

Bipartite networks are common in social science, but researchers often project data on unipartite networks for analysis. This new model uncovers patterns across node types, uses covariates to explain ties, and fits efficiently. Read the full paper here: www.cambridge.org/core/journal...

Currently in FirstView: In “A Statistical Model of Bipartite Networks: Application to Cosponsorship in the United States Senate,” @adelineylo.bsky.social, Santiago Olivella, and Kosuke Imai develop a statistical model of bipartite networks and offer an open-source software package for researchers.

GNNs are advantageous because they can be trained, saved, and deployed on new data, and they can also generate synthetic data. The paper uses the militarized international disputes dataset to illustrate potential applications. Read the paper here: www.cambridge.org/core/journal...

Currently in FirstView: In “Generative AI and Topological Data Analysis of Longitudinal Panel Data,” Badredine Arfi constructs an approach to analysing longitudinal panel data which combines topological data analysis and generative AI applied to graph neural networks (GNNs).

Probabilistic Record Linkage Using Pretrained Text Embeddings | Political Analysis | Cambridge Core Probabilistic Record Linkage Using Pretrained Text Embeddings

The package is demonstrated using several political examples where researchers may wish to join messy data. The fuzzylink package outperforms existing methods and even allows researchers to link datasets across languages. You can read the full paper here: www.cambridge.org/core/journal...

Currently in FirstView: In “Probabilistic Record Linkage Using Pretrained Text Embeddings,” @joeornstein.bsky.social introduces the R package fuzzylink and shows how to incorporate pretrained text embeddings into probabilistic record linkage procedure.

Decomposing Network Influence: Social Influence Regression | Political Analysis | Cambridge Core Decomposing Network Influence: Social Influence Regression

The authors apply the SIR model to data on monthly conflict events between countries, highlighting the model’s ability to illustrate complex influence patterns within networks by linking them to specific covariates. You can read the full paper here: www.cambridge.org/core/journal...

Currently in FirstView: In “Decomposing Network Influence: Social Influence Regression,” Shahryar Minhas and Peter Hoff introduce the social influence regression (SIR) model. The SIR model is for relational data that incorporates exogenous covariates into the estimation of influence patterns.

Explaining Differences in Voting Patterns across Voting Domains Using Hierarchical Bayesian Models | Political Analysis | Cambridge Core Explaining Differences in Voting Patterns across Voting Domains Using Hierarchical Bayesian Models

Using House procedural vs final passage votes, the model shows that minority-party members and legislators from moderate constituencies are most likely to shift positions across domains. You can read the full paper here: www.cambridge.org/core/journal...

Currently in FirstView: In “Explaining Differences in Voting Patterns across Voting Domains Using Hierarchical Bayesian Models,” Erin Lipman, Scott Moser, and Abel Rodriguez extend spatial voting models with a hierarchical Bayesian approach that estimates legislators’ ideal points.

Measuring Media Criticism with ALC Word Embeddings | Political Analysis | Cambridge Core Measuring Media Criticism with ALC Word Embeddings

This is validated using Arabic-language media published during the Arab Spring. Existing expert-based indices perform less well in stable autocracies, failing to detect short-term or subtle variations in media criticism. You can read the full paper here: www.cambridge.org/core/journal...

Currently in FirstView: In “Measuring Media Criticism with ALC Word Embeddings,” @cbarrie.bsky.social, Neil Ketchley, @aasiegel.bsky.social, and Mossaab Bagdouri introduce a method for estimating media criticism using à la carte word embeddings which requires only minimal computational resources.

An Expert-Sourced Measure of Judicial Ideology | Political Analysis | Cambridge Core An Expert-Sourced Measure of Judicial Ideology

The advantages are validated on a set of appellate decisions. These ideology estimates predict outcomes more accurately than existing appellate measures, and can inform debates on the nature of judicial ideology and decision-making. You can read the full paper here: www.cambridge.org/core/journal...

Currently in FirstView: In “An Expert-Sourced Measure of Judicial Ideology,” @kevinlcope.bsky.social develops a method for estimating the ideology of federal judges. He introduces the Jurist-Derived Judicial Ideology Score (JuDJIS) which is based on over 20,000 evaluations by a sample of jurists.

Moral Foundation Measurements Fail to Converge on Multilingual Party Manifestos | Political Analysis | Cambridge Core Moral Foundation Measurements Fail to Converge on Multilingual Party Manifestos

The authors replicate a study on parties’ use of moral foundations and show how different measurements can lead to opposite effect directions. They also offer best practices for studying moral foundations in political texts. Read the full paper here: www.cambridge.org/core/journal...

Currently in FirstView: “Moral Foundation Measurements Fail to Converge on Multilingual Party Manifestos.” @marvins.bsky.social and @fhopp.bsky.social examine 810 party manifestos in 4 languages to study how different instruments lead to different results for extracting moral foundations.

Detecting Formatted Text: Data Collection Using Computer Vision | Political Analysis | Cambridge Core Detecting Formatted Text: Data Collection Using Computer Vision

The method is demonstrated by extracting agenda items from city council meeting minutes. This workflow can accurately extract subsections of text from a document and required only a few hand labeled documents to train. You can read the full paper here: www.cambridge.org/core/journal...

Currently in FirstView: In “Detecting Formatted Text: Data Collection Using Computer Vision,” Jonathan Colner describes a workflow process for structured text extraction using free software. This method is useful for poorly-formatted sources that require researchers to extract each item by hand.

Bin-Conditional Conformal Prediction of Fatalities from Armed Conflict | Political Analysis | Cambridge Core Bin-Conditional Conformal Prediction of Fatalities from Armed Conflict

They use BCCP to forecast fatalities from armed conflicts and demonstrate that it provides well-calibrated uncertainty estimates. The authors also provide guidance and an R package for the BCCP algorithm. You can read the paper here: www.cambridge.org/core/journal...

Currently in FirstView: “Bin-Conditional Conformal Prediction of Fatalities from Armed Conflict” by David Randahl, Jonathan P. Williams, and Håvard Hegre. The authors discuss bin-conditional conformal prediction (BCCP) as an alternative to models that lack uncertainty estimates.

Balancing Precision and Retention in Experimental Design | Political Analysis | Cambridge Core Balancing Precision and Retention in Experimental Design

The authors replicate existing experiments and find that precision gains from block-randomized or pre-post designs can withstand sample loss that may arise during implementation. You can read the full paper here: www.cambridge.org/core/journal...

Currently in FirstView: In “Balancing Precision and Retention in Experimental Design,” @gustavodiaz.org and Erin Rossiter study how experimental design choices can increase precision when estimating treatment effects. Specifically, they examine block-randomized and pre-post designs.

Estimating the Local Average Treatment Effect Without the Exclusion Restriction | Political Analysis | Cambridge Core Estimating the Local Average Treatment Effect Without the Exclusion Restriction

The CPW estimator is demonstrated using a replication of a survey experiment, and shows stronger treatment effects than previously found. This suggests that meaningful effects can be missed using alternative approaches. You can read the full paper here: www.cambridge.org/core/journal...

Currently in FirstView: "Estimating the Local Average Treatment Effect Without the Exclusion Restriction." @zmarkovich.bsky.social introduces the Compliance Probability Weighting estimator, which enables inference about the LATE without relying on monotonicity or principal ignorability.

Measuring the Quality of Answers in Political Q&As with Large Language Models | Political Analysis | Cambridge Core Measuring the Quality of Answers in Political Q&As with Large Language Models

While some answers have only a weak semantic connection to questions, they are generally relevant. They also find meaningful correlations between the quality of answers and the party affiliation of the MPs asking the questions. You can read the paper here: www.cambridge.org/core/journal...

Currently in FirstView: In “Measuring the Quality of Answers in Political Q&As with Large Language Models,” @rmichaelalvarez.bsky.social and Jacob Morrier develop an approach for measuring the quality of answers in Q&A sessions using data from the Question Period in the Canadian House of Commons.

What to Observe When Assuming Selection on Observables | Political Analysis | Cambridge Core What to Observe When Assuming Selection on Observables

The authors discuss diagnostic tools to identify problems with estimation methods. Using two applied examples, they recommend researchers consider many estimation methods and model specifications and encourage open reporting. You can read the paper here: www.cambridge.org/core/journal...

Currently in FirstView: In “What to Observe When Assuming Selection on Observables,” Kevin M. Quinn, Guoer Liu, Lee Epstein, and Andrew Martin clarify how most estimators justified by a selection-on-observables assumption are special cases of a general weighting estimator.

Accessibility and Equity in the Research Process: Gender Bias in Elite Interview Recruitment | Political Analysis | Cambridge Core Accessibility and Equity in the Research Process: Gender Bias in Elite Interview Recruitment

Counter to expectations, they find that elites are more likely to schedule an interview when outreach comes from a female alias. This suggests that qualitative interviews may be limited by gender biases. You can read the paper here: www.cambridge.org/core/journal...

Currently in FirstView: In “Accessibility and Equity in the Research Process: Gender Bias in Elite Interview Recruitment,” Margaret A. T. Kenney and John Salchak study how researcher identity affects the research process. Specifically, they look at how this influences elite interview recruitment.