Lionel Tabourier
- Statistical and Nonlinear Physics top 5%
- Sociology and Political Science
- Artificial Intelligence
- Computer Networks and Communications
- Transportation top 10%
- Co-authors
- Renaud LambiotteAnne-Sophie LibertJean‐Charles DelvenneCamille RothFernando PeruaniMatthieu LatapyStéphane HallegatteJean‐Philippe Cointet
- Topics
- Complex Network Analysis Techniques (11 papers)Opinion Dynamics and Social Influence (9 papers)Advanced Graph Neural Networks (2 papers)
- Partner nations
- FranceBelgiumUnited Kingdom
In The Last Decade
Lionel Tabourier
14 papers receiving 253 citations
Peers
Comparison fields: 5 of 86
- Statistical and Nonlinear Physics 113
- Sociology and Political Science 57
- Artificial Intelligence 46
- Computer Networks and Communications 44
- Transportation 33
Countries citing papers authored by Lionel Tabourier
This map shows the geographic impact of Lionel Tabourier'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 Lionel Tabourier with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lionel Tabourier more than expected).
Fields of papers citing papers by Lionel Tabourier
This network shows the impact of papers produced by Lionel Tabourier. 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 Lionel Tabourier. The network helps show where Lionel Tabourier may publish in the future.
Co-authorship network of co-authors of Lionel Tabourier
This figure shows the co-authorship network connecting the top 25 collaborators of Lionel Tabourier. A scholar is included among the top collaborators of Lionel Tabourier 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 Lionel Tabourier. Lionel Tabourier is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 13 | |
| 2 | 9 | |
| 3 | 1 | |
| 4 | 0 | |
| 5 | 94 | |
| 6 | 17 | |
| 7 | RankMerging: Learning-to-rank in large-scale social networks (extended version). | 2 |
| 8 | A Data-Driven Analysis to Question Epidemic Models for Citation Cascades on the Blogosphere | 1 |
| 9 | 47 | |
| 10 | 4 | |
| 11 | 18 | |
| 12 | 17 | |
| 13 | 19 | |
| 14 | 16 | |
| 15 | 6 |
About Lionel Tabourier
Lionel Tabourier is a scholar working on Statistical and Nonlinear Physics, Transportation and Modeling and Simulation, having authored 15 papers that have together received 264 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (11 papers), Opinion Dynamics and Social Influence (9 papers) and Advanced Graph Neural Networks (2 papers). The work is most often cited by research in Statistical and Nonlinear Physics (113 citations), Transportation (33 citations) and Modeling and Simulation (12 citations). Lionel Tabourier has collaborated with scholars based in France, Belgium and United Kingdom. Frequent co-authors include Renaud Lambiotte, Anne-Sophie Libert, Jean‐Charles Delvenne, Camille Roth, Fernando Peruani, Matthieu Latapy, Stéphane Hallegatte, Jean‐Philippe Cointet, Fanny Henriet and Bivas Mitra. Their work appears in journals such as PLoS ONE, Machine Learning and Computer Networks.
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.