Cécile Bothorel

678 citations
7 papers · 166 · h-index 4

Impact in

Papers in

Cécile Bothorel

7 papers receiving 164 citations

Peers

Cécile Bothorel
Comparison fields: 5 of 50
  • Statistical and Nonlinear Physics 123
  • Artificial Intelligence 93
  • Computer Networks and Communications 25
  • Computer Vision and Pattern Recognition 21
  • Information Systems 23
Replace Nazanin Alipourfard with:
Nazanin Alipourfard United States
Suman Kundu India
Yanbo Liang China
François Théberge Canada
Ying Sha China
Matthias Broecheler United States
Mohit Kumar India
Timothy La Fond United States
Chengyao Chen Hong Kong
Konstantin Kutzkov Denmark
Cécile Bothorel relative to Nazanin Alipourfard United States Nazanin Alipourfard's profile →
Citations per field
00.5×4.3×
Nazanin Alipourfard · 1×
Citations per year

Countries citing papers authored by Cécile Bothorel

Since Specialization
Citations

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

Fields of papers citing papers by Cécile Bothorel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 6 scholars most cited alongside Cécile Bothorel, 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 Cécile Bothorel Line = papers co-authored together Cécile Bothorel links everyone, so they are left out of the graph.

All Works

7 of 7 papers shown
#Work
1 2015137
2 201317
3
Big Data - State of the Art
20134
4 20233
5 20062
6 20212
7 20201

About Cécile Bothorel

Cécile Bothorel is a scholar working on Statistical and Nonlinear Physics, Artificial Intelligence, Computer Vision and Pattern Recognition, Computer Networks and Communications and Molecular Biology, having authored 7 papers that have together received 166 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (3 papers), Opinion Dynamics and Social Influence (3 papers), Advanced Graph Neural Networks (2 papers), Sharing Economy and Platforms (1 paper), Cloud Computing and Resource Management (1 paper), Bayesian Modeling and Causal Inference (1 paper), FinTech, Crowdfunding, Digital Finance (1 paper) and Data Visualization and Analytics (1 paper). The work is most often cited by research in Statistical and Nonlinear Physics (123 citations), Artificial Intelligence (93 citations), Computer Networks and Communications (25 citations), Computer Vision and Pattern Recognition (21 citations) and Information Systems (23 citations). Cécile Bothorel has collaborated with scholars based in France, Sweden and Türkiye. Frequent co-authors include Matteo Magnani, Barbora Micenková, F. Poulet, Sébastien George, Philippe Lenca and Romain Billot. Their work appears in journals such as Network Science, Neurocomputing, ACM Transactions on Intelligent Systems and Technology, Social Network Analysis and Mining and Revue française de gestion.

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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