Mathieu Génois

571 citations
16 papers · 307 · h-index 9

Impact in

Papers in

Mathieu Génois

16 papers receiving 305 citations

Peers

Mathieu Génois
Comparison fields: 5 of 68
  • Modeling and Simulation 70
  • Statistical and Nonlinear Physics 160
  • Earth-Surface Processes 48
  • Computational Mathematics 3
  • Transportation 31
Replace Dimitri Volchenkov with:
Dimitri Volchenkov Germany
Robbert Fokkink Netherlands
Shupeng Gao China
Ning Ning Chung Singapore
Jian‐Yue Guan China
Naoya Fujiwara Japan
Cuihua Wang China
Jean-Gabriel Young United States
Lasko Basnarkov North Macedonia
Pierre‐André Noël Canada
Mathieu Génois relative to Dimitri Volchenkov Germany Dimitri Volchenkov's profile →
Citations per field
00.5×9.6×
Dimitri Volchenkov · 1×
Citations per year

Countries citing papers authored by Mathieu Génois

Since Specialization
Citations

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

Fields of papers citing papers by Mathieu Génois

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Mathieu Génois, 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 Mathieu Génois Line = papers co-authored together Mathieu Génois links everyone, so they are left out of the graph.

All Works

16 of 16 papers shown
#Work
1 201570
2 201547
3 201447
4 201235
5 202232
6 201314
7 201610
8 201610
9 20168
10 20228
11 20238
12 20236
13 20204
14 20164
15 20243
16 20201

About Mathieu Génois

Mathieu Génois is a scholar working on Statistical and Nonlinear Physics, Modeling and Simulation, Computer Networks and Communications, Sociology and Political Science and Experimental and Cognitive Psychology, having authored 16 papers that have together received 307 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (10 papers), Opinion Dynamics and Social Influence (8 papers), COVID-19 epidemiological studies (3 papers), Mental Health Research Topics (2 papers), Aeolian processes and effects (2 papers), Human Mobility and Location-Based Analysis (2 papers), Evolutionary Game Theory and Cooperation (2 papers) and Hydrology and Sediment Transport Processes (1 paper). The work is most often cited by research in Modeling and Simulation (70 citations), Statistical and Nonlinear Physics (160 citations), Earth-Surface Processes (48 citations), Computational Mathematics (3 citations) and Transportation (31 citations). Mathieu Génois has collaborated with scholars based in France, Germany and Italy. Frequent co-authors include Christian L. Vestergaard, Alain Barrat, Pascal Hersen, Guillaume Grégoire, Ciro Cattuto, Eugenio Valdano, Taro Takaguchi, Mikko Kivelä, Laëtitia Gauvin and Márton Karsai. Their work appears in journals such as Physical review. E, Nature Communications, PLoS Computational Biology, European Journal of Applied Mathematics and Communications Physics.

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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