Pascal Pons
Impact in
- Statistical and Nonlinear Physics top 0.5%
- Complex Network Analysis Techniques
- Opinion Dynamics and Social Influence
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- Mental Health Research Topics
Papers in
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- Complex Network Analysis Techniques 4
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- Peer-to-Peer Network Technologies 2
- Co-authors
- Matthieu Latapy (3 shared papers)Jérôme Galtier (1 shared paper)Jingbo Shang (1 shared paper)Po‐Ru Loh (1 shared paper)Iain Kilty (1 shared paper)Emilio Luque (1 shared paper)Andrew Hill (1 shared paper)Eva C. Guinan (1 shared paper)
In The Last Decade
Pascal Pons
8 papers receiving 2.4k citations
Pascal Pons's Hit Papers
Peers
Comparison fields: 5 of 185
- Statistical and Nonlinear Physics 1.3k
- Experimental and Cognitive Psychology 320
- Artificial Intelligence 576
- Transportation 108
- Computer Networks and Communications 339
Countries citing papers authored by Pascal Pons
This map shows the geographic impact of Pascal Pons'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 Pascal Pons with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pascal Pons more than expected).
Fields of papers citing papers by Pascal Pons
This network shows the impact of papers produced by Pascal Pons. 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 Pascal Pons. The network helps show where Pascal Pons may publish in the future.
Co-authors
The 17 scholars most cited alongside Pascal Pons, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Computing Communities in Large Networks Using Random Walks Hit paper breakdown → | 2005 | 1354 |
| 2 | Computing Communities in Large Networks Using Random Walks Hit paper breakdown → | 2006 | 1071 |
| 3 | 2010 | 30 | |
| 4 | 2017 | 15 | |
| 5 | 1970 | 12 | |
| 6 | 2006 | 10 | |
| 7 | 1999 | 8 | |
| 8 | Les syndiqués en France, 1990-2006 | 2007 | 3 |
| 9 | 2021 | 0 |
About Pascal Pons
Pascal Pons is a scholar working on Statistical and Nonlinear Physics, Computer Networks and Communications, Computational Theory and Mathematics, Communication and Political Science and International Relations, having authored 9 papers that have together received 2.5k indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (4 papers), Peer-to-Peer Network Technologies (2 papers), Education, sociology, and vocational training (1 paper), Wikis in Education and Collaboration (1 paper), Graph theory and applications (1 paper), Multiculturalism, Politics, Migration, Gender (1 paper), Agriculture and Rural Development Research (1 paper) and Advanced Graph Theory Research (1 paper). The work is most often cited by research in Statistical and Nonlinear Physics (1.3k citations), Experimental and Cognitive Psychology (320 citations), Artificial Intelligence (576 citations), Transportation (108 citations) and Computer Networks and Communications (339 citations). Pascal Pons has collaborated with scholars based in France, Hungary and Cameroon. Frequent co-authors include Matthieu Latapy, Jérôme Galtier, Jingbo Shang, Po‐Ru Loh, Iain Kilty, Emilio Luque, Andrew Hill, Eva C. Guinan, Karim R. Lakhani and Ana Cortés. Their work appears in journals such as Theoretical Computer Science, Journal of Graph Algorithms and Applications, GigaScience, Lecture notes in computer science and Observatorio (OBS*).
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.