bibliometrix: An R-tool for comprehensive science mapping analysis

By M. Aria, Corrado Cuccurullo. J. Informetrics, 2017

13,488 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems and Management

View Paper: https://www.semanticscholar.org/paper/aa59bd28fb4ca88a8c5ad1ce81943b385090cd77

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Nooria Yari
2. Vanessa P. G. Bretas
3. Erik Lankut
4. Usama Awan
5. José A. Folgado-Fernández
6. Marina Dabic
7. Pedro R. Palos-Sanchez
8. Rosa Palladino

In Computer Vision and Pattern Recognition

1. Nooria Yari
2. Vanessa P. G. Bretas
3. Erik Lankut
4. Usama Awan
5. José A. Folgado-Fernández
6. Marina Dabic
7. Pedro R. Palos-Sanchez
8. Rosa Palladino

In Information Systems and Management

1. Nooria Yari
2. Vanessa P. G. Bretas
3. Erik Lankut
4. Usama Awan
5. José A. Folgado-Fernández
6. Marina Dabic
7. Pedro R. Palos-Sanchez
8. Rosa Palladino

Citations in the corpus

• Bibliometric Analysis using Bibliometrix an R Package (2018, background): “Aria and Cuccurullo (2017), stated that bibliometric analysis is a cumbersome activity, which contains many producers.”
• The role of digital innovation in knowledge management systems: A systematic literature review (2021, methodology): “Bibliometric testing enables “ transparent ” as well as “ reproducible ” reviews (Aria & Cuccurullo, 2017, p. 959), giving safer results in the collection of scientific documents and news, without the risk of ignoring the most relevant contributions, regardless of the date of publication.”