Ginestra Bianconi
- Statistical and Nonlinear Physics top 0.05%
- Molecular Biology top 5%
- Computer Networks and Communications top 1%
- Cognitive Neuroscience top 2%
- Computational Theory and Mathematics top 0.5%
- Co-authors
- Albert-Ĺaszló BarabásiMatteo MarsiliYamir MorenoChristoph RahmedeKartik AnandMaziar NekoveeGiulia MenichettiJoaquı́n J. Torres
- Topics
- Complex Network Analysis Techniques (122 papers)Opinion Dynamics and Social Influence (69 papers)Topological and Geometric Data Analysis (31 papers)
- Cited by
- Statistical and Nonlinear PhysicsCondensed Matter PhysicsComputational Theory and Mathematics
- Partner nations
- United KingdomItalyUnited States
In The Last Decade
Ginestra Bianconi
189 papers receiving 9.1k citations
Hit Papers
Peers
Comparison fields: 5 of 194
- Statistical and Nonlinear Physics 5.6k
- Molecular Biology 1.4k
- Computer Networks and Communications 1.4k
- Cognitive Neuroscience 1.1k
- Computational Theory and Mathematics 963
Countries citing papers authored by Ginestra Bianconi
This map shows the geographic impact of Ginestra Bianconi'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 Ginestra Bianconi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ginestra Bianconi more than expected).
Fields of papers citing papers by Ginestra Bianconi
This network shows the impact of papers produced by Ginestra Bianconi. 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 Ginestra Bianconi. The network helps show where Ginestra Bianconi may publish in the future.
Co-authorship network of co-authors of Ginestra Bianconi
This figure shows the co-authorship network connecting the top 25 collaborators of Ginestra Bianconi. A scholar is included among the top collaborators of Ginestra Bianconi 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 Ginestra Bianconi. Ginestra Bianconi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 2 | |
| 3 | 1 | |
| 4 | 5 | |
| 5 | 24 | |
| 6 | 11 | |
| 7 | 5 | |
| 8 | 8 | |
| 9 | 49 | |
| 10 | 5 | |
| 11 | 0 | |
| 12 | 4 | |
| 13 | 22 | |
| 14 | 78 | |
| 15 | 8 | |
| 16 | 10 | |
| 17 | 16 | |
| 18 | Dynamics of Ranking Processes in Complex Systems | 53 |
| 19 | 492 | |
| 20 | Toward an information theory of complex networks | 2 |
About Ginestra Bianconi
Ginestra Bianconi is a scholar working on Statistical and Nonlinear Physics, Condensed Matter Physics and Computational Theory and Mathematics, having authored 192 papers that have together received 9.4k indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (122 papers), Opinion Dynamics and Social Influence (69 papers) and Topological and Geometric Data Analysis (31 papers). The work is most often cited by research in Statistical and Nonlinear Physics (5.6k citations), Condensed Matter Physics (918 citations) and Computational Theory and Mathematics (963 citations). Ginestra Bianconi has collaborated with scholars based in United Kingdom, Italy and United States. Frequent co-authors include Albert-Ĺaszló Barabási, Matteo Marsili, Yamir Moreno, Christoph Rahmede, Kartik Anand, Maziar Nekovee, Giulia Menichetti, Joaquı́n J. Torres, Vito Latora and S. N. Dorogovt︠s︡ev. Their work appears in journals such as Nature, Science and Proceedings of the National Academy of Sciences.
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.