Graduate Student Posters

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(How) Do Elections Build States? Evidence from Liberian Electoral Administration

Jeremy Bowles (Harvard University)

Abstract: In contexts where the state otherwise has limited reach, effective electoral administration permits the projection of state authority and increases levels of state-citizen interaction....

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A General Method for Detecting & Characterizing Interference in Field Experiments

Connor Jerzak (Harvard University)

Abstract: With the rise of online social networks, there has been growing interest in modeling how experimental units influence each another---a phenomenon known as "interference'' in the causal inference literature. Current models for interference generally requires knowledge of the way in which units are connected. Yet, in most field experiments, such data is unavailable. In this paper, we propose a...

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A New Multilevel-Based Indicator for Party System Nationalization

Kazuma Mizukoshi (University College London)

Abstract: “Science is impossible without an evolving network of stable measures” (Wright 1997: 33), but to what extent should measures be stable? Though measures seem still stable as...

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A Variable Selection Approach to Spillovers

Gustavo Diaz (University of Illinois, Urbana–Champaign)

Abstract: Spillovers or interference feature in many questions of interest in the social sciences. Current approaches to analyze spillovers in experiments assume that the researcher observes all relevant networks, implying knowledge of how units are connected. However,...

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A Win or a Flop? Identifying and Estimating Unintended Protest Costs in Measuring Success Outcomes

Kimberly Turner (Southern Illinois University, Carbondale)

Abstract: How we measure protest success and how to identify and measure the lagged effects of movements has long besieged the field. Estimating the full impact of a movement, both its intended and unintended consequences, is undermined by the lack of consensus on...

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Agnostic Sensitivity Analysis

Christopher Schwarz (New York University)

Abstract: The threat of endogeneity is ubiquitous within applied empirical research. A `near Bayesian' method of sensitivity analysis is developed and implemented, overcoming a number of difficulties with existing approaches. The procedure targets the distribution of possible causal...

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Analyzing Gendered & Raced Editorial Scrutiny of Lawmakers in the U.S. and U.K.

Julia Bourkland and Vanessa Cruz Nichols (Indiana University)

Abstract: Content analyses in gender and politics scholarship find that female elites are often discussed in different and degrading ways in news media compared to their male counterparts, with additional intra-group differences between white female elites and female elites of color. Feminist political scientists have long critiqued the way women in...

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Attributable Risk of Race: Detecting Partisan and Racial Gerrymandering

Sidak Yntiso and Sanford Gordon (New York University)

Abstract: How can we measure racial gerrymandering? Isolating racially disparate impacts of redistricting has proven difficult as sophisticated mapmakers can...

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Beyond Topics: Semi-Supervised Learning for Texts From a Measurement Perspective

Shiyao Liu (Massachusetts Institute of Technology)

Abstract: This project proposes a new methodological framework to use text data as a measurement in political science. Despite the abundance of text data available nowadays, conversion of text data into a measurement for a political concept remains a challenge that prevents...

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Bias-Corrected Crosswise Estimators for Sensitive Inquiries

Yuki Atsusaka (Rice University), Randy Stevenson (Rice University) and Ahra Wu (Dartmouth College)

Abstract: The crosswise model is an increasingly popular survey technique to elicit candid answers from respondents...

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Causal Inference in Difference-in-Differences Designs under Uncertainty in Counterfactual Trends

Thomas Leavitt (Columbia University)

Abstract: Difference-in-Differences (DID) is a popular method for design-based causal inference. Design-based methods typically quantify uncertainty in inferences from a sample to a population via a sampling mechanism and from observed to counterfactual outcomes via an assignment mechanism. The...

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Causal Inference Under Temporal and Spatial Interference

Ye Wang (New York University)

Abstract: Many social events and policies generate spillover effects in both time and space. Their occurrence influences not only the outcomes of interest in the future, but also these outcomes in nearby areas. In this paper, I propose a semi-parametric approach to estimate the direct and indirect/...

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Certain. Wrong. Misinformed? Evaluating Survey-Based Measures of Political Misperceptions

Matthew Graham (Yale University)

Abstract: Survey measures of the public's factual beliefs suggest widespread misinformation on politically relevant matters of fact: not only do many Americans not only choose incorrect responses, but...

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Changing the Dialogue: Candidate Position-Taking in Primary Elections

Rachel Porter, Sarah Treul and Maura McDonald (University of North Carolina)

Abstract: The record-high number of women who ran for the U.S. Congress during the midterm elections led many journalists to...

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Cheap Talk or Circuit to the Legislature: Why Do Corporations Express Public Support for and Opposition Against Free Trade?

Dahyun Choi (Princeton University)

Abstract: Studies of lobbying demonstrate that sending costly signals can further enhance the credibility of the information conveyed by firms, and this characteristic of lobbying has made scholars assume that entering into the lobbying market is the most effective channel for firms to influence...

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Clustering Large-Scale Ballot Data With Varying Choice Sets

Shiro Kuriwaki (Harvard University)

Abstract: Election scholars increasingly analyze large cast vote records (ballot image logs) to measure ticket splitting and ideological coherence in actual voter behavior. Election administrators also store cast vote records to detect election fraud and audit results. Although clustering methods...

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Collective Property Rights Reduce Deforestation in the Brazilian Amazon

Kathryn Baragwanath and Ella Bayi (University of California, San Diego)

Abstract: In this paper, we draw on common-pool resource theory to argue that indigenous territories, when granted full property...

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Conjoint Analysis in Studying Descriptive Representation

Laura Felone, Khasan Redjabov and Eli August (University of Wisconsin)

Abstract: We replicate Teele et al.’s (2018) substantively important question about political representation with a recent...

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Contrastive Multiple Component Analysis (cMCA): Applying the Contrastive Learning Method to Identify Political Subgroups

Tzu-Ping Liu and Takanori Fujiwara (University of California, Davis)

Abstract: Ideal point estimation and dimensionality reduction have long been utilized to simplify and cluster complex, high-dimensional political data (e.g., roll-call votes, surveys, and texts) for use in (preliminary) analysis and...

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Decoding Propaganda Slogans in China: Reading Between the Lines Using Word Embeddings

Yin Yuan (University of California, San Diego)

Abstract: Propaganda slogans in China (a.k.a. “catchphrases” or “tifa”) are widely believed to be artifacts of propaganda aimed at indoctrinating the general public that convey little substantive political or policy information. This paper intends to show instead that these...

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Diffusion of Cybersecurity Policies

Nadiya Kostyuk (University of Michigan, Ann Arbor)

Abstract: One of the most important developments of the last two decades has been the spread of national cybersecurity policies that affect millions of people globally. Yet, researchers know relatively little about this phenomenon. I study cybersecurity policy diffusion...

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Distances in Latent Space: A Novel Approach to Analyzing Conjoints

Simon Hoellerbauer (University of North Carolina, Chapel Hill)

Abstract: Recent work (Abramson, Kocak, and Magazinnik, n.d.) has shown the potential pitfalls of using conjoint analysis to understand aggregate preferences over alternative profiles. Adapting recent work that frames conjoint analysis in an IRT...

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Donation Dynamics: Do Critical Campaign Events Influence Contributions?

Seo-young Silvia Kim (California Institute of Technology)

Abstract: What events motivate individual campaign contributions? Using the 2016 campaign finance data from the Federal Election Commission as a daily time-series, I test the hypothesis that if presidential donors are either instrumental or momentum-driven, they...

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Don’t Know, Don’t Care: Non-Attitudes in African Public Opinion

Blair Read and Paige Bollen (Massachusetts Institute of Technology)

Abstract: Public opinion data can contain a wealth of information about how citizens evaluate and participate in politics. Yet, often respondents refuse to answer survey questions, or simply respond “don’t know” when asked about their opinion...

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Estimating Heterogeneous Effect on Clustered Data Using Mixed-Effects Model

Junlong Zhou (New York University)

Abstract: Estimating the heterogeneous treatment effect is essential to assess the generality and mechanism of randomized experiments. In this paper, we propose an extension of the regression forest combining mixed-effects to analyze heterogeneous treatment effect using aggregated data sets. We show that including mixed-effects can improve estimation by accounting for the cluster-level...

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Estimating Historical Election Results Under Counterfactual Electoral Systems

Samuel Baltz (University of Michigan)

Abstract: Despite the salience and importance of electoral system reform, both in the political science literature and in the contemporary politics of many democracies, little direct attention has been paid to the following question: how might the results of a specific election have been...

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Estimating Population Quantities From Multiple Data Sources Using the Structural Tensor Factorization

Soichiro Yamauchi (Harvard University)

Abstract: Estimating population quantities such as public opinions from survey data is a fundamental task in many social science studies. In political science, there is a growing interest in estimating public opinions at the level smaller than the entire nation, such as states (Lax and Phillips...

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Estimating the Dark Figure of Crime Using Bayesian Additive Regression Trees Plus Poststratification (BARP)

Isabel Laterzo (University of North Carolina, Chapel Hill)

Abstract: Studies of both crime victimization and violence often suffer from demonstrably unreliable crime figures. Consequently, researchers typically use homicide rates as an indicator to reflect all types of violence, despite this figure’s biases. The...

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Extracting Political Events From Text Using Grammatical Dependency Parsing and Machine Learning

Andrew Halterman (Massachusetts Institute of Technology)

Abstract: This paper introduces a method that automatically extracts political events from text using grammatical parsing and machine learning. Much of the scientifically useful information about what political actors are doing is locked away in text. To extract this...

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Finding Social Media Trolls: Dynamic Keyword Selection Methods for Rapidly Evolving Online Debates

Maya Srikanth, Anqi Liu, Nicholas Adams-Cohen, Anima Anandkumar and R. Michael Alvarez (California Institute of Technology)

Abstract: Online harassment is a significant social problem. Prevention of online harassment requires rapid detection of harassing, offensive, and negative social media posts. In this paper, we propose the use of word embedding...

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