Michael Mäs

2.1k citations
40 papers · 1.4k · 1 hit paper · h-index 16

Impact in

Papers in

Michael Mäs

39 papers receiving 1.3k citations

Michael Mäs's Hit Papers

Models of Social Influence: Towards the Next Frontiers 2017 · 387 citations
3870+3+6Years since publication100200300

Peers

Michael Mäs
Comparison fields: 5 of 113
  • Statistical and Nonlinear Physics 821
  • Communication 276
  • Sociology and Political Science 668
  • Modeling and Simulation 45
  • Management Science and Operations Research 93
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Citations per field
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Citations per year

Countries citing papers authored by Michael Mäs

Since Specialization
Citations

This map shows the geographic impact of Michael Mäs'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 Michael Mäs with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Mäs more than expected).

Fields of papers citing papers by Michael Mäs

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael Mäs. 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 Michael Mäs. The network helps show where Michael Mäs may publish in the future.

Co-authors

The 25 scholars most cited alongside Michael Mäs, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Michael Mäs Line = papers co-authored together Michael Mäs links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 40 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Models of Social Influence: Towards the Next Frontiers
Hit paper breakdown →
2017387
2 2013159
3 2010149
4 201294
5 201776
6 201668
7 201557
8 201654
9 200844
10 201338
11 200735
12 201831
13 202227
14 201425
15 202222
16 200518
17 202014
18 20179
19 20169
20 20148

About Michael Mäs

Michael Mäs is a scholar working on Sociology and Political Science, Statistical and Nonlinear Physics, Communication, Political Science and International Relations and Safety Research, having authored 40 papers that have together received 1.4k indexed citations. Recurring topics across this work include Opinion Dynamics and Social Influence (24 papers), Evolutionary Game Theory and Cooperation (12 papers), Complex Network Analysis Techniques (10 papers), Social Media and Politics (8 papers), Experimental Behavioral Economics Studies (5 papers), Social and Intergroup Psychology (5 papers), Electoral Systems and Political Participation (4 papers) and Misinformation and Its Impacts (4 papers). The work is most often cited by research in Statistical and Nonlinear Physics (821 citations), Communication (276 citations), Sociology and Political Science (668 citations), Modeling and Simulation (45 citations) and Management Science and Operations Research (93 citations). Michael Mäs has collaborated with scholars based in Netherlands, Germany and Switzerland. Frequent co-authors include Andreas Flache, Dirk Helbing, Jan Lorenz, Thomas Feliciani, Edmund Chattoe‐Brown, Guillaume Deffuant, Sylvie Huet, Károly Takács, Karen A. Jehn and Stefano Balietti. Their work appears in journals such as Journal of Artificial Societies and Social Simulation, PLoS ONE, Computational and Mathematical Organization Theory, Social Science Research and KZfSS Kölner Zeitschrift für Soziologie und Sozialpsychologie.

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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