Lukas Isermann

Lukas Isermann

Doctoral Researcher

University of Mannheim

Biography

I am a Political Scientist specializing in quantitative analyses of survey and textual data. My research focuses on party competition and strategic issue emphasis, with experience in electoral behaviour, group-based appeals, and democratic norms. In my dissertation, I examine how political parties emphasize climate change in parliamentary debates, applying text-as-data methods to speeches from 27 European countries.

I am a student at the Mannheim Graduate School of Social Sciences (GESS), affiliated with the Mannheimer Zentrum für Europäische Sozialforschung (MZES), and a lecturer at the University of Mannheim, teaching courses on hierarchical statistical analysis in Stata and R, as well as substantial courses on climate change attitudes and political participation.

My work has been published in Electoral Studies and Politische Vierteljahresschrift, with additional manuscripts under review. I have reviewed for Party Politics, Political Research Exchange, Political Research Quarterly and Politische Vierteljahresschrift, and I have developed two R software packages published on CRAN.

Interests
  • NLP
  • Statistics
  • Political Psychology
  • Party Competition
  • Climate Change
Education
  • PhD in Political Science, ongoing

    University of Mannheim

  • MA in Political Science, 2020

    University of Mannheim & University of Aarhus

  • BA in Political Science, 2018

    University of Mannheim

Peer-reviewed articles

(2024). Committed Democrats? How Trade-off Specific Cues Affect Expressions of Support for Liberal and Democratic Principles. Politische Vierteljahresschrift.

Cite DOI PDF OSF

Software

(2024). archiveRetriever. R package version 0.4.0.

Cite DOI CRAN github

(2023). handcodeR. R package version 0.1.2.

Cite Project DOI CRAN github

Blog posts

(2022). APIs for social scientists: A collaborative review. https://paulcbauer.github.io/apis_for_social_scientists_a_review/.

Cite github

Conference Presentations and Talks

Analyzing Party Competition on Climate Change: A Machine Learning Approach
Presentation at COMPTEXT Conference 2024
From Valence to Positional Conflict? How Parties’ compete on Climate Change
Presentation at COMPTEXT Conference 2024
Just like me: Evidence on group-cue based voting from Germany
Presentation at EPSA Conference 2023
Strategic Issue Emphasis? Comparing easy read and regular manifestos using NLP
Presentation at COMPTEXT Conference 2023
Roundtable event "APIs for social scientists: A collaborative review"
MZES Social Science Data Lab

Contact

  • A5, 6
    68159 Mannheim
  • Enter Building A and take the stairs to Office A328 on Floor 3