Diego Garlaschelli
- Statistical and Nonlinear Physics top 0.2%
- Economics and Econometrics top 0.5%
- Finance top 2%
- Sociology and Political Science top 5%
- Molecular Biology
- Co-authors
- Maria I. LoffredoTiziano SquartiniGuido CaldarelliGiorgio FagioloStefano BattistonL. PietroneroGiulio CiminiFabio Saracco
- Topics
- Complex Network Analysis Techniques (53 papers)Complex Systems and Time Series Analysis (30 papers)Opinion Dynamics and Social Influence (19 papers)
- Partner nations
- ItalyNetherlandsUnited Kingdom
In The Last Decade
Diego Garlaschelli
75 papers receiving 3.3k citations
Hit Papers
Peers
Comparison fields: 5 of 164
- Statistical and Nonlinear Physics 1.8k
- Economics and Econometrics 1.4k
- Finance 325
- Sociology and Political Science 315
- Molecular Biology 287
Countries citing papers authored by Diego Garlaschelli
This map shows the geographic impact of Diego Garlaschelli'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 Diego Garlaschelli with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Diego Garlaschelli more than expected).
Fields of papers citing papers by Diego Garlaschelli
This network shows the impact of papers produced by Diego Garlaschelli. 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 Diego Garlaschelli. The network helps show where Diego Garlaschelli may publish in the future.
Co-authorship network of co-authors of Diego Garlaschelli
This figure shows the co-authorship network connecting the top 25 collaborators of Diego Garlaschelli. A scholar is included among the top collaborators of Diego Garlaschelli 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 Diego Garlaschelli. Diego Garlaschelli is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 11 | |
| 5 | 2 | |
| 6 | 7 | |
| 7 | 3 | |
| 8 | 0 | |
| 9 | 0 | |
| 10 | 7 | |
| 11 | 0 | |
| 12 | 8 | |
| 13 | 14 | |
| 14 | 1 | |
| 15 | 135 | |
| 16 | 7 | |
| 17 | 9 | |
| 18 | Unbiased community detection for correlation matrices | 2 |
| 19 | Rewiring World Trade. Part I: A Binary Network Analysis | 3 |
| 20 | 36 |
About Diego Garlaschelli
Diego Garlaschelli is a scholar working on Statistical and Nonlinear Physics, Economics and Econometrics and Computational Theory and Mathematics, having authored 85 papers that have together received 3.4k indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (53 papers), Complex Systems and Time Series Analysis (30 papers) and Opinion Dynamics and Social Influence (19 papers). The work is most often cited by research in Statistical and Nonlinear Physics (1.8k citations), Economics and Econometrics (1.4k citations) and Finance (325 citations). Diego Garlaschelli has collaborated with scholars based in Italy, Netherlands and United Kingdom. Frequent co-authors include Maria I. Loffredo, Tiziano Squartini, Guido Caldarelli, Giorgio Fagiolo, Stefano Battiston, L. Pietronero, Giulio Cimini, Fabio Saracco, Andrea Gabrielli and Matteo Barigozzi. 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.