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Marcel Neunhoeffer

PhD Candidate

University of Mannheim

Biography

I am a PhD Candidate and Research Associate at the chair of Political Science, Quantitative Methods in the Social Sciences at the University of Mannheim.

My research focuses on political methodology, where I am specifically interested in the application of deep learning algorithms to social science problems. My substantive interests include voting behavior, political campaigns and forecasting elections. For my research I implemented a large scale field experiment within a partisan campaign, I am also interested in Social Media data and contributed to the research with a large Voting Advice Application.

My work has been published in the Politische Vierteljahresschrift (PVS) and in Political Analysis. I also had the opportunity to present some of my recent work at the International Methods Colloquium.

Furthermore, I am co-founder, contributor and the visualizationist of zweitstimme.org – a website that communicated a scientific forecast for the German Federal election 2017 to a broad audience.

Interests

  • Machine Learning
  • Deep Learning
  • (Differential) Privacy
  • (Field-) Experimental Research
  • Big Data
  • Data Visualization
  • Voting Behavior

Education

  • PhD Candidate, Present

    Graduate School of Economic and Social Sciences, University of Mannheim

  • M.A. in Political Science, 2016

    University of Mannheim

  • B.A. in Governance and Public Policy, 2013

    University of Passau

Publications & Work in Progress

Forecasting Elections in Multi-Party Systems: A Bayesian Approach Combining Polls and Fundamentals

We offer a dynamic Bayesian forecasting model for multi-party elections. It com- bines data from published pre-election public opinion …

How Cross-Validation Can Go Wrong and What to Do About it.

The introduction of new “machine learning” methods and terminology to political science complicates the interpretation of results. Even …

Zweitstimme.org. A structural-dynamic forecasting model for German federal elections

We present results of an ex-ante forecast of party-specific vote shares at the German Federal Election 2017. To that end, we combine …

A Partisan Treatment in a High Salience Election: Evidence from a Field Experiment in Germany

How do partisan campaigns influence voting behavior in high salience elections? In 2016, I conducted a field experiment in the German …

Teaching

I am a teaching instructor for the following courses at University of Mannheim:

  • Spring 2018: Tutorial Advanced Quantitative Methods, Graduate (in English), Syllabus

  • Fall 2018: Tutorial Multivariate Analyses, Graduate (in English), Syllabus, Evaluation

  • Spring 2018: Tutorial Advanced Quantitative Methods, Graduate (in English), Syllabus, Evaluation

  • Fall 2017: Tutorial Multivariate Analyses, Graduate (in English), Syllabus, Evaluation

  • Spring 2017: Tutorial Advanced Quantitative Methods, Graduate (in English), Syllabus, Evaluation

  • Fall 2016: Tutorial Multivariate Analyses, Graduate (in English), Syllabus, Evaluation

Testimonials:

Wonderful! This tutorial and it’s corresponding course were my favorite. Marcel is a great teacher, a great speaker, and creates a great classroom environment. He is very supportive and encouraging. I always enjoyed attending and wish there were future tutorials and courses to attend.


Marcel is an excellent tutor who knows his stuff very well an animates us students to further engage with quantitative methods. Great Job!


Marcel was one of the best tutors I had in my 5 years at German universities. He was very helpful, open for questions, friendly towards students and easy to approach.


E xcellent course. I felt myself getting more and more employable from one session to the next. Really cool stuff we learn!


Furthermore, I have been teaching at University of Applied Sciences Ludwigshafen:

Besides that, I am also a instructor of professional training workshops:

  • February 2018: Introduction to R, 1 day workshop, Geschäftsstelle für Qualitätssicherung Hessen, Frankfurt

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