Andrea Capocci

17 papers receiving 1.1k citations

Hit Papers

Scale-Free Networks from Varying Vertex Intrinsic Fitness20022026201020182002100200300400500

Peers

Andrea Capocci
Comparison fields: 5 of 96
  • Statistical and Nonlinear Physics 856
  • Molecular Biology 194
  • Sociology and Political Science 142
  • Computer Networks and Communications 132
  • Artificial Intelligence 132
Replace Vinko Zlatić with:
Vinko Zlatić Croatia
J. G. Oliveira Portugal
Holger Ebel Germany
Saulo D. S. Reis Brazil
Maria I. Loffredo Italy
Jon Kleinberg United States
Jérôme Kunegis Germany
Clémence Magnien France
Julian Sienkiewicz Poland
François Fouss Belgium
Andrea Capocci relative to Vinko Zlatić Croatia Vinko Zlatić's profile →
Citations per field
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Vinko Zlatić · 1×
Citations per year

Countries citing papers authored by Andrea Capocci

Since Specialization
Citations

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

Fields of papers citing papers by Andrea Capocci

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Andrea Capocci

This figure shows the co-authorship network connecting the top 25 collaborators of Andrea Capocci. A scholar is included among the top collaborators of Andrea Capocci 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 Andrea Capocci. Andrea Capocci is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

17 of 17 papers shown
#WorkIndexed citations
1 2
2 14
3 4
4 4
5 22
6 72
7 26
8
Preferential attachment in the growth of social networks: the case of Wikipedia
20
9 7
10 190
11 28
12 183
13 67
14 10
15
Scale-Free Networks from Varying Vertex Intrinsic Fitnessbreakdown →
502
16 11
17 2

About Andrea Capocci

Andrea Capocci is a scholar working on Statistical and Nonlinear Physics, Communication and Computer Science Applications, having authored 17 papers that have together received 1.2k indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (15 papers), Opinion Dynamics and Social Influence (11 papers) and Peer-to-Peer Network Technologies (3 papers). The work is most often cited by research in Statistical and Nonlinear Physics (856 citations), Communication (114 citations) and Computer Science Applications (50 citations). Andrea Capocci has collaborated with scholars based in Italy, Switzerland and Brazil. Frequent co-authors include Guido Caldarelli, Paolo De Los Rios, Miguel A. Muñoz, Francesca Colaiori, Vito D. P. Servedio, Ginestra Bianconi, Luciana S. Buriol, Debora Donato, Stefano Leonardi and Diego Garlaschelli. Their work appears in journals such as Physical Review Letters, Nature Physics and Physica A Statistical Mechanics and its Applications.

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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