Rosaria Lombardo
- Food Science top 5%
- Statistics and Probability top 5%
- Artificial Intelligence
- Economics and Econometrics
- Social Psychology
- Co-authors
- Eric J. BehPieter M. KroonenbergBiagio SimonettiJacqueline J. MeulmanRichard D. De VeauxYoshio TakaneFaculteit der Sociale WetenschappenJean-François Durand
- Topics
- Sensory Analysis and Statistical Methods (37 papers)Advanced Statistical Methods and Models (12 papers)Spectroscopy and Chemometric Analyses (8 papers)
- Partner nations
- ItalyAustraliaSouth Africa
In The Last Decade
Rosaria Lombardo
47 papers receiving 425 citations
Peers
Comparison fields: 5 of 122
- Food Science 204
- Statistics and Probability 87
- Artificial Intelligence 33
- Economics and Econometrics 28
- Social Psychology 27
Countries citing papers authored by Rosaria Lombardo
This map shows the geographic impact of Rosaria Lombardo'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 Rosaria Lombardo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rosaria Lombardo more than expected).
Fields of papers citing papers by Rosaria Lombardo
This network shows the impact of papers produced by Rosaria Lombardo. 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 Rosaria Lombardo. The network helps show where Rosaria Lombardo may publish in the future.
Co-authorship network of co-authors of Rosaria Lombardo
This figure shows the co-authorship network connecting the top 25 collaborators of Rosaria Lombardo. A scholar is included among the top collaborators of Rosaria Lombardo 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 Rosaria Lombardo. Rosaria Lombardo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 3 | |
| 5 | 0 | |
| 6 | 4 | |
| 7 | 3 | |
| 8 | 13 | |
| 9 | 2 | |
| 10 | Modelling Trends in Ordered Three-Way Non-Symmetrical Correspondence Analysis | 1 |
| 11 | 3 | |
| 12 | 14 | |
| 13 | 2 | |
| 14 | Correspondence Analysis: Theory, Practice and New Strategies | 88 |
| 15 | 10 | |
| 16 | 1 | |
| 17 | 16 | |
| 18 | 8 | |
| 19 | 10 | |
| 20 | 2 |
About Rosaria Lombardo
Rosaria Lombardo is a scholar working on Computational Mathematics, Food Science and Statistics and Probability, having authored 53 papers that have together received 442 indexed citations. Recurring topics across this work include Sensory Analysis and Statistical Methods (37 papers), Advanced Statistical Methods and Models (12 papers) and Spectroscopy and Chemometric Analyses (8 papers). The work is most often cited by research in Computational Mathematics (18 citations), Food Science (204 citations) and Statistics and Probability (87 citations). Rosaria Lombardo has collaborated with scholars based in Italy, Australia and South Africa. Frequent co-authors include Eric J. Beh, Pieter M. Kroonenberg, Biagio Simonetti, Jacqueline J. Meulman, Richard D. De Veaux, Yoshio Takane, Faculteit der Sociale Wetenschappen, Jean-François Durand, Pasquale Dal Sasso and Trevor J. Ringrose. Their work appears in journals such as Psychometrika, Food Quality and Preference and Social Indicators Research.
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.