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Political Analysis

@polanalysis.bsky.social
1.2K followers 11 following 154 posts

Official Journal of the Society for Political Methodology www.cambridge.org/core/journals/pol…

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Political Analysis @polanalysis.bsky.social · 13/08/2026
They show that partial contestation constitutes a form of sample selection and illustrate their approach by analyzing the 2017 and 2019 U.K. parliamentary elections. Read the full paper here: www.cambridge.org/core/journal...
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Let Them Eat Pie: Addressing Sample Selection in Multiparty Elections | Political Analysis | Cambridge Core
Let Them Eat Pie: Addressing Sample Selection in Multiparty Elections
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Political Analysis @polanalysis.bsky.social · 13/08/2026
Currently in FirstView: In “Let Them Eat Pie: Addressing Sample Selection in Multiparty Elections,” Ali Kagalwala, @tmqm.bsky.social, Guy Whitten, and Yongzhi Xu introduce a novel maximum likelihood approach that accounts for the biases that come from sample selection in a compositional setting.
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Political Analysis @polanalysis.bsky.social · 06/08/2026
They adapt their approach for regression-discontinuity designs and show how prognosis weighting can avoid both false negatives and false positives. Read the full paper here: www.cambridge.org/core/journal...
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The Power of Prognosis: Improving Covariate Balance Tests with Outcome Information | Political Analysis | Cambridge Core
The Power of Prognosis: Improving Covariate Balance Tests with Outcome Information
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Political Analysis @polanalysis.bsky.social · 06/08/2026
Currently in FirstView: In “The Power of Prognosis: Improving Covariate Balance Tests with Outcome Information,” Clara Bicalho, Adam Bouyamourn, and Thad Dunning show how balance tests can lead to false conclusions and develop tests that upweight covariates associated with outcomes.
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Political Analysis @polanalysis.bsky.social · 14/07/2026
The authors develop a partial identification approach, monotone EI, and illustrate it using county-level data on partisanship and COVID-19 vaccines. You can read the paper here: www.cambridge.org/core/journal...
cambridge.org
Monotone Ecological Inference | Political Analysis | Cambridge Core
Monotone Ecological Inference
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Political Analysis @polanalysis.bsky.social · 14/07/2026
Currently in FirstView: In “Monotone Ecological Inference,” Hadi Elzayn, @jacobsgoldin.bsky.social, Cameron Guage, Daniel Ho, and Claire Morton characterize the biases of, and relationships among ecological inference (EI) estimators for identifying group means and differences.
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Political Analysis @polanalysis.bsky.social · 25/06/2026
The authors provide two stylized examples illustrating this framework, establish key elements of the analysis, and discuss the interpretation of results under STUVA as well as a weaker assumption (NURVA). Read the full paper here: www.cambridge.org/core/journal...
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On the Foundations of the Design-Based Approach | Political Analysis | Cambridge Core
On the Foundations of the Design-Based Approach
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Political Analysis @polanalysis.bsky.social · 25/06/2026
Currently in FirstView: In “On the Foundations of the Design-Based Approach,” P. M. Aronow, Austin Jang, and @mollyow.bsky.social propose a design-based framework for analyzing randomized trials and survey sampling that avoids strong claims about the data-generating process.
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Political Analysis @polanalysis.bsky.social · 11/06/2026
TRACE is the total effect of treatment in the group that would realize a particular value of the relevant post-treatment variable. Unlike other approaches, TRACE does not require strong and untestable assumptions. Read the paper here: www.cambridge.org/core/journal...
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Post-Treatment Problems: What Can We Say about the Effect of a Treatment among Sub-Groups Who (Would) Respond in Some Way? | Political Analysis | Cambridge Core
Post-Treatment Problems: What Can We Say about the Effect of a Treatment among Sub-Groups Who (Would) Respond in Some Way?
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Political Analysis @polanalysis.bsky.social · 11/06/2026
Currently in FirstView: In “Post-Treatment Problems: What Can We Say about the Effect of a Treatment among Sub-Groups Who (Would) Respond in Some Way?,” Chad Hazlett, Nina McMurry, and Tanvi Shinkre propose the treatment reactive average causal effect (TRACE).
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Political Analysis @polanalysis.bsky.social · 04/06/2026
Using a simulation and two replication studies, they demonstrate that this approach adheres to the compositional data constraints and offers a more accurate interpretation of estimated treatment effects for proportional outcomes. You can read the paper here: www.cambridge.org/core/journal...
cambridge.org
Estimating Treatment Effects on Proportions with Synthetic Controls | Political Analysis | Cambridge Core
Estimating Treatment Effects on Proportions with Synthetic Controls
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Political Analysis @polanalysis.bsky.social · 04/06/2026
Currently in FirstView: In “Estimating Treatment Effects on Proportions with Synthetic Controls,” @bogatyrev.bsky.social and @lstoetze.bsky.social examine synthetic control methods (SCMs) and make the case for jointly estimating synthetic controls across multiple compositional outcomes.
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Political Analysis @polanalysis.bsky.social · 28/05/2026
They validate this method using pre-election polling from the 2022 Michigan midterm and find that their calibrated MRP estimates reduce error by as much as two-thirds. You can read the full paper here: www.cambridge.org/core/journal...
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Improving Small-Area Estimates of Public Opinion by Calibrating to Known Population Quantities | Political Analysis | Cambridge Core
Improving Small-Area Estimates of Public Opinion by Calibrating to Known Population Quantities
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Political Analysis @polanalysis.bsky.social · 28/05/2026
Currently in FirstView: In “Improving Small-Area Estimates of Public Opinion by Calibrating to Known Population Quantities,” @wpmarble.bsky.social and Josh Clinton provide a framework for incorporating known population data to improve estimates of small subgroups in MRP models.
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Political Analysis @polanalysis.bsky.social · 21/05/2026
The paper walks through three studies where text is used to quantify attitudes and actions. Ultimately, the paper argues that expression is sufficiently demanding that it should be understood as a form of action. Read the paper here: www.cambridge.org/core/journal...
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Text as Behavior | Political Analysis | Cambridge Core
Text as Behavior
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Political Analysis @polanalysis.bsky.social · 21/05/2026
Currently in FirstView: In “Text as Behavior,” @owasow.bsky.social proposes using features of open-ended tasks to study text as behavior. Stats like the number of characters can approximate effort and significantly improve estimation.
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Political Analysis @polanalysis.bsky.social · 15/05/2026
Their framework, UNITAS, reduces the dependence of inferences on specific datasets, cut-offs, magnitude-of-change and time-window assumptions, while efficiently handling missingness and measurement uncertainty. You can read the paper here: www.cambridge.org/core/journal...
cambridge.org
Democracy Manifest or Democracy Latent? A Unified Framework for Identifying Regime Types and Transitions | Political Analysis | Cambridge Core
Democracy Manifest or Democracy Latent? A Unified Framework for Identifying Regime Types and Transitions
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Political Analysis @polanalysis.bsky.social · 15/05/2026
Currently in FirstView: In “Democracy Manifest or Democracy Latent? A Unified Framework for Identifying Regime Types and Transitions,” @omerorsun.bsky.social and Muhammet A. Bas develop and validate a framework to study regimes that addresses measurement uncertainty and missing data.
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Political Analysis @polanalysis.bsky.social · 08/05/2026
The authors introduce a methodology that integrates LMs and structured coding schemes to classify open-ended survey responses cost-effectively and find that LMs can capture democratic perceptions and handle data abstractions. Read the full paper here: www.cambridge.org/core/journal...
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Using Multilingual Language Technology to Classify Open-Ended Survey Responses: Conceptions of Democracy in a Cross-Cultural Survey Setting | Political Analysis | Cambridge Core
Using Multilingual Language Technology to Classify Open-Ended Survey Responses: Conceptions of Democracy in a Cross-Cultural Survey Setting
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Political Analysis @polanalysis.bsky.social · 08/05/2026
Currently in FirstView: In “Using Multilingual Language Technology to Classify Open-Ended Survey Responses: Conceptions of Democracy in a Cross-Cultural Survey Setting,” S. Dahlberg, L. Dürlich, S. Axelsson, Y. Zhao, and J. Nivre examine the use of LMs in analyzing open-ended survey responses.
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Political Analysis @polanalysis.bsky.social · 30/04/2026
By adaptively adjusting randomization probabilities via Thompson sampling, the method efficiently identifies the contexts in which the focal attribute has its most positive and most negative effects. You can read the paper here: www.cambridge.org/core/journal...
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Adaptive Randomization in Conjoint Survey Experiments | Political Analysis | Cambridge Core
Adaptive Randomization in Conjoint Survey Experiments
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Political Analysis @polanalysis.bsky.social · 30/04/2026
Currently in FirstView: In “Adaptive Randomization in Conjoint Survey Experiments,” @jennahgosciak.bsky.social, @dmolitor.bsky.social, and @ianlundberg.bsky.social develop an adaptive design for conjoint experiments that summarizes the range of effects of one attribute as a function of all others.
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Political Analysis @polanalysis.bsky.social · 15/04/2026
All models consistently attributed more liberal ideologies to women while racial associations differed by model. They conclude that using these models political content analysis may unknowingly introduce model-specific confounds. Read the paper here: www.cambridge.org/core/journal...
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From Faces to Politics: Vision-Language Models (Sometimes) Link Visual Demographic Characteristics to Ideological Labels | Political Analysis | Cambridge Core
From Faces to Politics: Vision-Language Models (Sometimes) Link Visual Demographic Characteristics to Ideological Labels
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Political Analysis @polanalysis.bsky.social · 15/04/2026
Currently in FirstView: In “From Faces to Politics: Vision-Language Models (Sometimes) Link Visual Demographic Characteristics to Ideological Labels,” S. Jeon, M. Lee, @jacobmontgomery.bsky.social, and @calvinklai.bsky.social ask how models use demographics as shortcuts for ideological attribution.
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Political Analysis @polanalysis.bsky.social · 08/04/2026
They propose an assumption to account for nonignorable missingness in the outcome. Integrating this assumption with covariate information provides an identifiable method for estimating voter turnout. You can read the full paper here: www.cambridge.org/core/journal...
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Correcting Nonignorable Nonresponse Bias in Turnout Estimation Using Callback Data | Political Analysis | Cambridge Core
Correcting Nonignorable Nonresponse Bias in Turnout Estimation Using Callback Data
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Political Analysis @polanalysis.bsky.social · 08/04/2026
Currently in FirstView: In “Correcting Nonignorable Nonresponse Bias in Turnout Estimation Using Callback Data,” Xinyu Li, Naiwen Ying, Kendrick Qijun Li, Xu Shi, and Wang Miao look at the role of callback data as a way of adjusting for nonresponse bias in estimating voter turnout.
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Political Analysis @polanalysis.bsky.social · 01/04/2026
The authors offer a GP framework and highlight certain use cases. GPs have the ability to incorporate extrapolation uncertainty, widening intervals as predictions rely more heavily on assumptions beyond the observed support. Read the paper here: www.cambridge.org/core/journal...
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Inference at the Data’s Edge: Gaussian Processes for Estimation and Inference in the Face of Extrapolation Uncertainty | Political Analysis | Cambridge Core
Inference at the Data’s Edge: Gaussian Processes for Estimation and Inference in the Face of Extrapolation Uncertainty
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Political Analysis @polanalysis.bsky.social · 01/04/2026
Currently in FirstView: In “Inference at the Data’s Edge: Gaussian Processes for Estimation and Inference in the Face of Extrapolation Uncertainty,” Soonhong Cho, Doeun Kim, and Chad Hazlet illustrate the value of Gaussian Processes (GPs) for capturing counterfactual uncertainty. 
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Political Analysis @polanalysis.bsky.social · 25/03/2026
The model is validated with data on coalition government survival, showing that ignoring party-level dependencies can produce misleading conclusions at all levels of analysis. The paper also introduces an accompanying R package. You can read it here: www.cambridge.org/core/journal...
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A Multilevel Model for Coalition Governments: Uncovering Party-Level Dependencies Within and Between Governments | Political Analysis | Cambridge Core
A Multilevel Model for Coalition Governments: Uncovering Party-Level Dependencies Within and Between Governments
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Political Analysis @polanalysis.bsky.social · 25/03/2026
Currently in FirstView: In “A Multilevel Model for Coalition Governments: Uncovering Party-Level Dependencies Within and Between Governments,” Benjamin Rosche extends the Multiple Membership Multilevel Model to represent the multilevel structure of coalition government data.
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Political Analysis @polanalysis.bsky.social · 18/03/2026
The adjusted estimates show that congressional polarization and its increase over time are ever greater than previously thought, and the electoral penalty associated with ideological extremism is greater than previously thought. Read the paper here: www.cambridge.org/core/journal...
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Accounting for Protest Voting in the U.S. Congress | Political Analysis | Cambridge Core
Accounting for Protest Voting in the U.S. Congress
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Political Analysis @polanalysis.bsky.social · 18/03/2026
Currently in FirstView: In “Accounting for Protest Voting in the U.S. Congress,” Anthony Fowler and Jeffrey B. Lewis estimate a model of congressional voting that allows for non-ideological protest voting. This has significant implications for roll-call estimates of ideology.
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Political Analysis @polanalysis.bsky.social · 12/03/2026
The model offers insights about stability, the direction of causation between attitudes, and their relative influence. They use their model to show the role of ideology on attitudes toward government spending and immigration. Read the paper here: www.cambridge.org/core/journal...
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A Dynamic Discrete Choice Approach to Attitude Stability and Constraint | Political Analysis | Cambridge Core
A Dynamic Discrete Choice Approach to Attitude Stability and Constraint
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Political Analysis @polanalysis.bsky.social · 12/03/2026
Currently in FirstView: In “A Dynamic Discrete Choice Approach to Attitude Stability and Constraint,” @alecia-nepaul.bsky.social and Steven Stern introduce a discrete choice framework to identify influential attitudes within attitude systems.
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Political Analysis @polanalysis.bsky.social · 04/03/2026
The findings challenge Gamson’s law: the idea that cabinet ministries in multiparty democracies are distributed in proportion to seats. Because portfolio and seats are mutually dependent, ILR addresses concerns of bias and uncertainty. Read the paper here: www.cambridge.org/core/journal...
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Refining Gamson: The Isometric Log-Ratio Transformation and Portfolio Proportionality in Multiparty Governments | Political Analysis | Cambridge Core
Refining Gamson: The Isometric Log-Ratio Transformation and Portfolio Proportionality in Multiparty Governments
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Political Analysis @polanalysis.bsky.social · 04/03/2026
Currently in FirstView: in “Refining Gamson: The Isometric Log-Ratio Transformation and Portfolio Proportionality in Multiparty Governments,” Lanny Martin and Georg Vanberg propose the isometric log-ratio (ILR) as an alternative to the additive log-ratio (ALR) transformation.
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Political Analysis @polanalysis.bsky.social · 25/02/2026
They demonstrate the utility of their models by analyzing civil rights protests in the US. These models are useful because many datasets in political science are nested and can potentially have diffusion processes at multiple levels. Read the paper here: www.cambridge.org/core/journal...
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Modeling Hierarchical Spatial Interdependence for Limited Dependent Variables | Political Analysis | Cambridge Core
Modeling Hierarchical Spatial Interdependence for Limited Dependent Variables
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Political Analysis @polanalysis.bsky.social · 25/02/2026
Currently in FirstView: in “Modeling Hierarchical Spatial Interdependence for Limited Dependent Variables,” Ali Kagalwala and Kankyeul Yang propose a class of spatial hierarchical models with binary outcomes to account for spatially independent and spatially dependent unobserved group effects.
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Political Analysis @polanalysis.bsky.social · 18/02/2026
Using a dataset of all televised U.S. presidential debates from 1960 to 2020, the authors highlight many applications including forced alignment of audio text, speech characterization, and custom classification models. Read the paper here: www.cambridge.org/core/journal...
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Potential and Pitfalls of Audio as Data for Political Research: Alignment, Features, and Classification Models | Political Analysis | Cambridge Core
Potential and Pitfalls of Audio as Data for Political Research: Alignment, Features, and Classification Models
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Political Analysis @polanalysis.bsky.social · 18/02/2026
Currently in FirstView: in “Potential and Pitfalls of Audio as Data for Political Research: Alignment, Features, and Classification Models,” @r-mestre.bsky.social and Matt Ryan provide solutions to challenges encountered when analyzing audio data in political science.
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Political Analysis @polanalysis.bsky.social · 11/02/2026
In their replication, they show that the association between education and acquiescence is an artifact of low-quality survey responses. Scholars should be cautious about over-interpreting conditional effects in low-quality survey panels. Read the paper here: www.cambridge.org/core/journal...
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Survey Quality and Acquiescence Bias: A Cautionary Tale | Political Analysis | Cambridge Core
Survey Quality and Acquiescence Bias: A Cautionary Tale
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Political Analysis @polanalysis.bsky.social · 11/02/2026
Currently in FirstView: In “Survey Quality and Acquiescence Bias: A Cautionary Tale,” Andrés Cruz, Adam Bouyamourn, and @joeornstein.bsky.social discuss the dangers of drawing inferences from low-quality survey datasets. They replicate an experiment on acquiescence and misinformation.
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Political Analysis @polanalysis.bsky.social · 03/02/2026
ConfliBERT is open source and is easily deployed and replicable. It is significantly better on comparable, relevant quality metrics and faster than other LLMS that use decoder technologies with graphical processing units (GPUs). Read the full paper here: www.cambridge.org/core/journal...
cambridge.org
Extractive versus Generative Language Models for Political Conflict Text Classification | Political Analysis | Cambridge Core
Extractive versus Generative Language Models for Political Conflict Text Classification
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Political Analysis @polanalysis.bsky.social · 03/02/2026
Currently in FirstView: In “Extractive versus Generative Language Models for Political Conflict Text Classification,” P. Brandt, S. Alsarra, F. D’Orazio, @dagmarheintze.bsky.social, L. Khan, S. Meher, @javierosorio.bsky.social, & M. Sianan review and benchmark the ConfliBERT model.
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Political Analysis @polanalysis.bsky.social · 29/01/2026
The January 2026 issue of Political Analysis is out and currently free to read. Check it out now through the end of February!
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Political Analysis @polanalysis.bsky.social · 22/01/2026
Their BSA method is designed to address concerns about confounders that cannot be addressed by fixed effects. They illustrate this using a Monte Carlo simulation study and an empirical example on the effect of war on tax rates. Read the full paper here: www.cambridge.org/core/journal...
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Political Analysis @polanalysis.bsky.social · 22/01/2026
Currently in FirstView: In “Bayesian Sensitivity Analysis for Unmeasured Confounding in Causal Panel Data Models,” Licheng Liu and Teppei Yamamoto develop a Bayesian sensitivity analysis (BSA) method for causal panel data analysis.
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Political Analysis @polanalysis.bsky.social · 13/01/2026
They find that complex prompting strategies can lead to improved model performance. The authors also offer several recommendations for researchers using LLMs for stance detection in political texts. You can read the full paper here: www.cambridge.org/core/journal...
cambridge.org
Stay Tuned: Improving Sentiment Analysis and Stance Detection Using Large Language Models | Political Analysis | Cambridge Core
Stay Tuned: Improving Sentiment Analysis and Stance Detection Using Large Language Models
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Political Analysis @polanalysis.bsky.social · 13/01/2026
Currently in FirstView: In “Stay Tuned: Improving Sentiment Analysis and Stance Detection Using Large Language Model,” Max Griswold, Michael Robbins, and @sociologian.bsky.social evaluate fine-tuning strategies to improve LLM performance using social media data surrounding the 2020 election.
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Political Analysis @polanalysis.bsky.social · 06/01/2026
The Political Domain Enhanced BERT-based Algorithm for Textual Entailment (DEBATE) is benchmarked against other popular supervised classifiers. Ultimately, DEBATE is both efficient and completely open source. Read the paper here: www.cambridge.org/core/journal...
cambridge.org
Political DEBATE: Efficient Zero-Shot and Few-Shot Classifiers for Political Text | Political Analysis | Cambridge Core
Political DEBATE: Efficient Zero-Shot and Few-Shot Classifiers for Political Text
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