Matteo Magnani

2.9k citations
76 papers · 1.6k indexed · h-index 21

Matteo Magnani

73 papers receiving 1.5k citations

Peers

Matteo Magnani
Comparison fields: 5 of 162
  • Statistical and Nonlinear Physics 406
  • Signal Processing 128
  • Organic Chemistry 315
  • Computer Networks and Communications 208
  • Artificial Intelligence 247
Replace Junning Liu with:
Junning Liu China
Zheng Chen China
Ying Shen China
Jian‐Yun Nie Canada
David R. Nadeau United States
Krishnendu Chatterjee Austria
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Andrea Passerini Italy
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Citations per field
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Citations per year

Countries citing papers authored by Matteo Magnani

Since Specialization
Citations

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

Fields of papers citing papers by Matteo Magnani

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Matteo Magnani, 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 Matteo Magnani Line = papers co-authored together Matteo Magnani links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 20241
3 2020103
4 20206
5 20204
6
A Join Operator for Property Graphs
20174
7 201515
8
Diffusion Processes on Multilayer Networks.
20149
9
On multidimensional network measures
20134
10
Anytime skyline query processing for interactive systems
20124
11
#rescatemineros: global media events in the microblogging age
20112
12 200926
13 2008124
14 200836
15 20071
16
Uncertainty in data integration: current approaches and open problems.
200718
17 200652
18
Schema integration based on uncertain semantic mappings
20055
19 20041
20
A unified approach to structured, semistructured and unstructured data
20043

About Matteo Magnani

Matteo Magnani is a scholar working on Statistical and Nonlinear Physics, Signal Processing and Communication, having authored 76 papers that have together received 1.6k indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (29 papers), Opinion Dynamics and Social Influence (24 papers), Data Management and Algorithms (13 papers), Advanced Database Systems and Queries (10 papers), Semantic Web and Ontologies (8 papers), Social Media and Politics (6 papers), Microtubule and mitosis dynamics (5 papers) and Advanced Graph Neural Networks (5 papers). The work is most often cited by research in Statistical and Nonlinear Physics (406 citations), Signal Processing (128 citations) and Organic Chemistry (315 citations). Matteo Magnani has collaborated with scholars based in Italy, Sweden and Denmark. Frequent co-authors include Luca Rossi, Maurizio Botta, Danilo Montesi, Fabrizio Manetti, Mark E. Dickison, Cécile Bothorel, Barbora Micenková, Ira Assent, Stefano Rossi and Ruben Foresti. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.

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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