Lorenzo Malandri

724 citations
28 papers · 412 indexed · h-index 11
Topics
Topic Modeling (14 papers)Explainable Artificial Intelligence (XAI) (8 papers)Natural Language Processing Techniques (6 papers)

In The Last Decade

Lorenzo Malandri

27 papers receiving 401 citations

Peers

Lorenzo Malandri
Comparison fields: 5 of 75
  • Artificial Intelligence 225
  • Management Science and Operations Research 125
  • Finance 50
  • Information Systems 45
  • Economics and Econometrics 42
Replace Namhyoung Kim with:
Namhyoung Kim South Korea
Yunqi Li United States
Jiaao Chen United States
Alfonso Guarino Italy
Cristiane Neri Nobre Brazil
Tanveer Ahmed India
Sally Firmin Australia
Steven J. Jackson United States
Nicola Lettieri Italy
Chris Rose United States
Lorenzo Malandri relative to Namhyoung Kim South Korea Namhyoung Kim's profile →
Citations per field
00.5×4.0×
Namhyoung Kim · 1×
Citations per year

Countries citing papers authored by Lorenzo Malandri

Since Specialization
Citations

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

Fields of papers citing papers by Lorenzo Malandri

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lorenzo Malandri

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

All Works

20 of 20 papers shown
#WorkIndexed citations
1 8
2 2
3 1
4 5
5 64
6 14
7 9
8 41
9 3
10 9
11 1
12 3
13 10
14 1
15 5
16 42
17 40
18 3
19 2
20 21

About Lorenzo Malandri

Lorenzo Malandri is a scholar working on Artificial Intelligence, Information Systems and Management and Management Science and Operations Research, having authored 28 papers that have together received 412 indexed citations. Recurring topics across this work include Topic Modeling (14 papers), Explainable Artificial Intelligence (XAI) (8 papers) and Natural Language Processing Techniques (6 papers). The work is most often cited by research in Health Informatics (19 citations), Management Science and Operations Research (125 citations) and Artificial Intelligence (225 citations). Lorenzo Malandri has collaborated with scholars based in Italy, Singapore and United States. Frequent co-authors include Fabio Mercorio, Mario Mezzanzanica, Erik Cambria, Frank Xing, Carlotta Orsenigo, Carlo Vercellis, Yue Zhang, Noemi Gozzi, Alessandra Pedrocchi and Simone Merello. Their work appears in journals such as Applied Soft Computing, Decision Support Systems and Knowledge-Based Systems.

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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