Oliver Lang
I am a Ph.D. candidate in political science at the University of Wisconsin-Madison.
My research examines the production and consumption of propaganda under authoritarian rule.
Dissertation
Propaganda and the logic of competition in autocratic media markets
I study media markets and the supply of propaganda in authoritarian regimes. My dissertation project examines the origins and consequences of competition in the market for television news.
The central argument is that media market competition changes the audience for, as well the constraints on, regime propaganda: citizens skeptical of pro-regime messaging can seek out alternative, often apolitical, media; and absent the constraints of a skeptical audience, regimes can broadcast more biased propaganda yet will reach a smaller audience. This trade-off has implications both for the efficacy of propaganda and information control under autocracy, as well as the stability of authoritarian regimes.
I evaluate this argument using original data on 25 years of outlet competition in the market for television news across sixty-four autocracies, a content analysis of scraped newscasts from government channels, and cross-national survey data on news consumption.
Research
under review
Tribal voting in new democracies: evidence from 6 million Tunisian voter records
Are voters more likely to support candidates who share their tribal identity? Does this relationship hold even where tribal identity is not linked to party and electoral institutions? These questions are difficult to answer using observational data because of measurement challenges, selection problems, or both. We address these empirical obstacles and questions in Tunisia, where successive governments tried to marginalize tribal identity. We match a historical dictionary of tribes to surnames from the universe of both registered voters and candidates in Tunisia's 2018 municipal elections. We find that lists characterized by high "affinity," where candidates share a tribal identity with voters, outperform lists with lower affinity. Our findings suggests that tribal identity, despite decades of marginalization, was politically salient in these elections, which were widely judged to be free and fair, and that Tunisia's largest and best organized parties were the primary beneficiaries of this "tribal advantage."
under review
How Increasing Refugee Visibility on TV News Causes Viewers to Support Refugees More, but Like Them Less
As global refugee flows accelerate, so does local news coverage on the subject and the potential for major political consequences. In an analysis of all broadcasts of the most famous television news program in Germany 2013-2019, we first show observationally (through text and image analysis) that refugee coverage increases with immigration and is correlated in different ways with public opinion about refugees. Conditioning on these patterns, we then implement a nationally representative block randomized media experiment. We find that TV news coverage of refugees causes viewers to be more willing to donate money to pro-refugee organizations, but surprisingly to feel colder and more socially distant towards them. We discuss the far reaching consequences of this divergent pattern for the future of local politics in Germany and potentially around the world.
Who complies with censorship: evidence from Brazilian censorship directives
This project investigates compliance with censorship directives during Brazil's military dictatorship. Using newly digitized archives of censorship orders and newspaper content, we examine which outlets complied with state censorship demands and why.
The strategic origins of the Streisand Effect: evidence from censored newspaper in the GDR
This paper examines the strategic dynamics behind the Streisand Effect — when censorship attempts inadvertently increase attention to the censored content. Using archival data from East German newspapers, we analyze how state censors navigated this dilemma.
Teaching
Causal Inference
This course aims to give a comprehensive introduction to causal inference. Targeted at Data Science masters students in their second semester, the course introduces students to the potential outcomes and directed acyclic graph frameworks for formalizing the assumptions necessary to support causal claims. Emphasis is on the general logic of non-paramteric causal identification and design-based inference for causal estimands. By the end of the course, students should be able to formulate research designs constrained by the set of assumptions plausible for a specific empirical application. All classes divide time between theory and hands-on application in R and Python.
About
I am a doctoral candidate in the Department of Political Science at the University of Wisconsin-Madison, and a visiting researcher at the Hertie School of Governance in Berlin. My work spans comparative politics, political communication, and political economy.
My research is centered around three questions: How do autocratic regimes curtail the flow of information necessary for evaluating government performance? How do the institutions of autocratic governance constrain propaganda content? How does competition between media outlets shape coverage when markets are subject to government intervention?
Before coming to Madison, I completed my undergraduate studies in International and Middle Eastern Studies at the University of Washington.