D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Engineering and Technology D-index 60 Citations 14,211 183 World Ranking 622 National Ranking 12

Research.com Recognitions

Awards & Achievements

2020 - Fellow of American Physical Society (APS) Citation For major contributions to understanding the disorder effects in selfsimilar phenomena, particularly in real scalefree networks and in theoretical models

2020 - Member of Academia Europaea

Overview

What is he best known for?

The fields of study he is best known for:

  • Statistics
  • The Internet
  • Artificial intelligence

Guido Caldarelli focuses on Complex network, Social media, Financial market, Data science and The Internet. In the subject of general Complex network, his work in Fitness model is often linked to Money market, thereby combining diverse domains of study. His Social media research integrates issues from Social psychology, Misinformation and Advertising.

His study in Financial market is interdisciplinary in nature, drawing from both Volatility and Econometrics. Guido Caldarelli has included themes like Diversification, Fixed point, Competitive advantage and Industrial organization in his Data science study. Guido Caldarelli interconnects Market sentiment and Search engine in the investigation of issues within The Internet.

His most cited work include:

  • The spreading of misinformation online (744 citations)
  • Scale-Free networks from varying vertex intrinsic fitness (580 citations)
  • Scale-Free Networks: Complex Webs in Nature and Technology (537 citations)

What are the main themes of his work throughout his whole career to date?

His main research concerns Complex network, Statistical physics, Theoretical computer science, Econometrics and Systemic risk. His Complex network study focuses on Fitness model in particular. The study incorporates disciplines such as Fractal dimension, Fractal and Scaling in addition to Statistical physics.

The Theoretical computer science study combines topics in areas such as Structure and Bipartite graph. His studies in Econometrics integrate themes in fields like Financial market and Portfolio. Guido Caldarelli studies Systemic risk, focusing on Financial networks in particular.

He most often published in these fields:

  • Complex network (28.11%)
  • Statistical physics (13.82%)
  • Theoretical computer science (11.29%)

What were the highlights of his more recent work (between 2015-2021)?

  • Complex network (28.11%)
  • Financial networks (8.06%)
  • Systemic risk (9.45%)

In recent papers he was focusing on the following fields of study:

Guido Caldarelli mainly focuses on Complex network, Financial networks, Systemic risk, Econometrics and Theoretical computer science. His Complex network research is multidisciplinary, incorporating elements of Ecology, Financial contagion, Centrality, Distributed computing and Statistical physics. His Financial networks research is multidisciplinary, relying on both Balance sheet, Network topology, Interbank lending market and Financial system.

His work in Systemic risk covers topics such as Financial economics which are related to areas like Mutual fund. His study looks at the relationship between Econometrics and fields such as Stability, as well as how they intersect with chemical problems. The concepts of his Theoretical computer science study are interwoven with issues in Null and Bipartite graph.

Between 2015 and 2021, his most popular works were:

  • The spreading of misinformation online (744 citations)
  • Echo Chambers: Emotional Contagion and Group Polarization on Facebook. (138 citations)
  • The statistical physics of real-world networks (114 citations)

In his most recent research, the most cited papers focused on:

  • Statistics
  • Artificial intelligence
  • The Internet

Guido Caldarelli mostly deals with Complex network, Financial networks, Social media, Systemic risk and Advertising. His Complex network research incorporates themes from Centrality, Distributed computing, Statistical physics, Variety and Entropy. His Financial networks research includes elements of Network topology, Actuarial science, Monetary economics and Financial system.

His Social media study incorporates themes from Sentiment analysis and Information exchange. His Systemic risk study combines topics from a wide range of disciplines, such as Balance sheet, Stress test, Valuation and Credit risk. His Advertising study integrates concerns from other disciplines, such as Null model, Discounting and Misinformation.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Scale-Free Networks: Complex Webs in Nature and Technology

Guido Caldarelli.
(2007)

1313 Citations

The spreading of misinformation online

Michela Del Vicario;Alessandro Bessi;Fabiana Zollo;Fabio Petroni.
Proceedings of the National Academy of Sciences of the United States of America (2016)

1275 Citations

Scale-Free networks from varying vertex intrinsic fitness

G. Caldarelli;A. Capocci;P. De Los Rios;P. De Los Rios;M. A. Muñoz.
Physical Review Letters (2002)

867 Citations

DebtRank: Too Central to Fail? Financial Networks, the FED and Systemic Risk

Stefano Battiston;Michelangelo Puliga;Rahul Kaushik;Paolo Tasca.
Scientific Reports (2012)

715 Citations

A network analysis of the Italian overnight money market

Giulia Iori;Giulia De Masi;Ovidiu Vasile Precup;Giampaolo Gabbi;Giampaolo Gabbi.
Journal of Economic Dynamics and Control (2008)

617 Citations

Topology of correlation-based minimal spanning trees in real and model markets.

Giovanni Bonanno;Guido Caldarelli;Fabrizio Lillo;Rosario Nunzio Mantegna.
Physical Review E (2003)

514 Citations

Science vs Conspiracy: Collective Narratives in the Age of Misinformation

Alessandro Bessi;Mauro Coletto;George Alexandru Davidescu;Antonio Scala.
PLOS ONE (2015)

449 Citations

Detecting communities in large networks

Andrea Capocci;Vito D. P. Servedio;Guido Caldarelli;Francesca Colaiori.
Physica A-statistical Mechanics and Its Applications (2005)

447 Citations

Networks of equities in financial markets

G. Bonanno;G. Caldarelli;F. Lillo;S. Micciche.
European Physical Journal B (2004)

433 Citations

Preferential attachment in the growth of social networks: the internet encyclopedia Wikipedia.

Andrea Capocci;Vito D. P. Servedio;Francesca Colaiori;Luciana Buriol;Luciana Buriol.
Physical Review E (2006)

385 Citations

Best Scientists Citing Guido Caldarelli

Albert-László Barabási

Albert-László Barabási

Northeastern University

Publications: 83

Stefano Battiston

Stefano Battiston

Ca Foscari University of Venice

Publications: 59

Tao Zhou

Tao Zhou

University of Electronic Science and Technology of China

Publications: 58

Yi-Cheng Zhang

Yi-Cheng Zhang

University of Fribourg

Publications: 45

Fabrizio Lillo

Fabrizio Lillo

University of Bologna

Publications: 41

Ginestra Bianconi

Ginestra Bianconi

Queen Mary University of London

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János Kertész

János Kertész

Central European University

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Benjamin Miranda Tabak

Benjamin Miranda Tabak

Fundação Getulio Vargas

Publications: 34

Giorgio Fagiolo

Giorgio Fagiolo

Sant'Anna School of Advanced Studies

Publications: 31

J. Doyne Farmer

J. Doyne Farmer

University of Oxford

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Yamir Moreno

Yamir Moreno

University of Zaragoza

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Antonio Scala

Antonio Scala

National Academies of Sciences, Engineering, and Medicine

Publications: 28

Mason A. Porter

Mason A. Porter

University of California, Los Angeles

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Alex Arenas

Alex Arenas

Rovira i Virgili University

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Alessandro Vespignani

Alessandro Vespignani

Northeastern University

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Romualdo Pastor-Satorras

Romualdo Pastor-Satorras

Universitat Politècnica de Catalunya

Publications: 26

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking d-index is inferred from publications deemed to belong to the considered discipline.

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