Marcel Neunhoeffer

533 total citations
9 papers, 103 citations indexed

About

Marcel Neunhoeffer is a scholar working on Political Science and International Relations, Sociology and Political Science and Artificial Intelligence. According to data from OpenAlex, Marcel Neunhoeffer has authored 9 papers receiving a total of 103 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Political Science and International Relations, 3 papers in Sociology and Political Science and 3 papers in Artificial Intelligence. Recurrent topics in Marcel Neunhoeffer's work include Electoral Systems and Political Participation (4 papers), Data Analysis with R (2 papers) and Public Administration and Political Analysis (1 paper). Marcel Neunhoeffer is often cited by papers focused on Electoral Systems and Political Participation (4 papers), Data Analysis with R (2 papers) and Public Administration and Political Analysis (1 paper). Marcel Neunhoeffer collaborates with scholars based in Germany, United States and Switzerland. Marcel Neunhoeffer's co-authors include Sebastian Sternberg, Thomas Gschwend, Christian Arnold, Simon Munzert, Lukas F. Stoetzer, Roni Lehrer, Mark Bun, Marco Gaboardi and Wanrong Zhang and has published in prestigious journals such as European Journal of Political Research, Political Analysis and PS Political Science & Politics.

In The Last Decade

Marcel Neunhoeffer

9 papers receiving 93 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Marcel Neunhoeffer Germany	5	24	19	17	14	11	9	103
Sebastian Sternberg Germany	6	43 1.8×	14 0.7×	15 0.9×	17 1.2×	9 0.8×	8	88
Leonardo Ramos Brazil	5	34 1.4×	34 1.8×	13 0.8×	21 1.5×		25	117
Paul Scharre Russia	4	29 1.2×	13 0.7×	10 0.6×	10 0.7×		5	80
Lucy Campbell-Gillingham United Kingdom	3	5 0.2×	25 1.3×	5 0.3×	27 1.9×	3 0.3×	4	100
Abdurrahman Abdurrahman Indonesia	8	30 1.3×	43 2.3×	4 0.2×	58 4.1×	2 0.2×	83	211
Dirk Hartung United States	6	121 5.0×	99 5.2×	25 1.5×	12 0.9×	8 0.7×	16	188
Gaurav Mishra India	5	7 0.3×	18 0.9×	3 0.2×	11 0.8×		20	77
Marius Rohde Johannessen Norway	6	34 1.4×	9 0.5×	2 0.1×	25 1.8×	2 0.2×	26	122
Joris van Zundert Netherlands	8	4 0.2×	75 3.9×	3 0.2×	19 1.4×	4 0.4×	27	188
Jelena Mitrović Germany	9	25 1.0×	197 10.4×	6 0.4×	54 3.9×	5 0.5×	39	272

Countries citing papers authored by Marcel Neunhoeffer

Since Specialization

Citations

This map shows the geographic impact of Marcel Neunhoeffer's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Marcel Neunhoeffer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marcel Neunhoeffer more than expected).

Fields of papers citing papers by Marcel Neunhoeffer

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Marcel Neunhoeffer. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Marcel Neunhoeffer. The network helps show where Marcel Neunhoeffer may publish in the future.

Co-authorship network of co-authors of Marcel Neunhoeffer

This figure shows the co-authorship network connecting the top 25 collaborators of Marcel Neunhoeffer. A scholar is included among the top collaborators of Marcel Neunhoeffer based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Marcel Neunhoeffer. Marcel Neunhoeffer is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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9 of 9 papers shown

Arnold, Christian, et al.. (2024). The role of hyperparameters in machine learning models and how to tune them. Political Science Research and Methods. 12(4). 841–848. 35 indexed citations

Lehrer, Roni, et al.. (2024). Rallying around the leader in times of crises: The opposing effects of perceived threat and anxiety. European Journal of Political Research. 64(2). 697–718. 3 indexed citations

Bun, Mark, Marco Gaboardi, Marcel Neunhoeffer, & Wanrong Zhang. (2024). Continual Release of Differentially Private Synthetic Data from Longitudinal Data Collections. Proceedings of the ACM on Management of Data. 2(2). 1–26. 1 indexed citations

Neunhoeffer, Marcel, et al.. (2023). How to improve the substantive interpretation of regression results when the dependent variable is logged. Political Science Research and Methods. 13(1). 203–211. 4 indexed citations

Gschwend, Thomas, et al.. (2021). The Zweitstimme Model: A Dynamic Forecast of the 2021 German Federal Election. PS Political Science & Politics. 55(1). 85–90. 4 indexed citations

Neunhoeffer, Marcel, Thomas Gschwend, Simon Munzert, & Lukas F. Stoetzer. (2020). Ein Ansatz zur Vorhersage der Erststimmenanteile bei Bundestagswahlen. Politische Vierteljahresschrift. 61(1). 111–130. 1 indexed citations

Neunhoeffer, Marcel & Sebastian Sternberg. (2018). How Cross-Validation Can Go Wrong and What to Do About It. Political Analysis. 27(1). 101–106. 26 indexed citations

Stoetzer, Lukas F., Marcel Neunhoeffer, Thomas Gschwend, Simon Munzert, & Sebastian Sternberg. (2018). Forecasting Elections in Multiparty Systems: A Bayesian Approach Combining Polls and Fundamentals. Political Analysis. 27(2). 255–262. 19 indexed citations

Munzert, Simon, et al.. (2017). Zweitstimme.org. Ein strukturell-dynamisches Vorhersagemodell für Bundestagswahlen. Politische Vierteljahresschrift. 58(3). 418–441. 10 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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