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Hi there 👋

I'm Andrea De Angelis, currently an SNF Ambizione Researcher in the Department of Political Science at the University of Zurich. Welcome to my GitHub profile!

  • 🔭 I’m currently working on: The project “Political Misinformation in the Digital Age,” funded by the Swiss National Science Foundation. My research focuses on political misinformation, media change, dealignment, and the personalization of politics in European democracies.

  • 🌱 I’m currently learning: How to use LLMs for my teaching and research (ideas are welcome!).

  • 👯 I’m looking to collaborate on: Projects at the intersection of political science, computational methods, and digital media. I am especially interested in collaborations that explore the dynamics of political misinformation and media effects on electoral decisions.

  • 🤔 I’m looking for help with: Expanding my research in the area of political misinformation in a global context, especially studies outside the U.S. and Switzerland/Europe.

  • 💬 Ask me about: Electoral politics, media effects, political misinformation, and computational methods in social science research.

  • 📫 How to reach me: Email me at [email protected] or connect with me on LinkedIn.

  • Fun fact: I am training to run my first marathon!

Languages and Tools:

  • R, Python, HTML, CSS, HTTP, Git, LaTeX, Markdown, Stata, JAGS, Stan, MATLAB
  • Multilingual with proficiency in Italian, English, Spanish, plus some German, and French.

Recent Publications:

  • De Angelis A. and Vecchiato A. (2023). ”Panem et Circenses: Removing Political News to Generate Electoral Support, Evidence from Berlusconi’s Italy.” Fortcoming at the Italian Political Science Review.
  • De Angelis A. et al. (2022). “Political Misinformation in the Digital Age During a Pandemic: Partisanship Propaganda and Democratic Decision-Making.” OA Edited Volume at Frontiers in Political Science. Read the editorial here.
  • Garzia D. et al. (2021). “Leaders without Partisans: Dealignment, Media Change and the Personalization of Politics.” Colchester: Rowman & Littlefield/ECPR Press. OA version available at Cadmus.
  • De Angelis, A. (2020). “How Voters Distort their Perceptions and Why this Matters.“ In: Suhay, E., Grofman, B., and Trechsel, A., The Oxford Handbook of Electoral Persuasion, pp. 946-976. Pre-print available here, published version here.

Awards and Distinctions:

  • Gordon Smith and Vincent Wright Memorial Prize for the best papaer published on West European Politics (2022)
  • Swiss National Science Foundation Ambizione Grant (2022-2026)
  • Honorary mention for teaching excellence by the University of Lucerne (2022)

Andrea De Angelis's Projects

covidrtpcr icon covidrtpcr

Analysis of RT-PCR sensitivity by day since exposure or symptom onset

data icon data

Data and code behind the stories and interactives at FiveThirtyEight

deangelisa.github.io icon deangelisa.github.io

Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes

isss23 icon isss23

Material for the lecture "Introduction to Statistics for the Social Sciences"

ltta_workshop icon ltta_workshop

Companion repo for the EuroCSS 2018 workshop on Linguistic Temporal Trajectory Analysis

naive_context_sentiment icon naive_context_sentiment

Naive sentiment analysis in R: sensitive to valence shifters but not relying on punctuation of sentence boundaries

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