André Panisson

39 papers receiving 869 citations

Peers

André Panisson
Comparison fields: 5 of 105
  • Computational Mathematics 33
  • Transportation 140
  • Statistical and Nonlinear Physics 226
  • Health Informatics 22
  • Modeling and Simulation 58
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Hemank Lamba United States
Piotr Bródka Poland
Paramveer S. Dhillon United States
Giulio Rossetti Italy
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Katayoun Farrahi United Kingdom
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Citations per field
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Citations per year

Countries citing papers authored by André Panisson

Since Specialization
Citations

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

Fields of papers citing papers by André Panisson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 48 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2014162
2 2020100
3 201657
4 201651
5 201349
6 202148
7 201948
8 200543
9 201142
10 201339
11 200832
12 201532
13 202131
14 200624
15
Predicting City Poverty Using Satellite Imagery
201921
16 202021
17
Explainability Methods for Natural Language Processing: Applications to Sentiment Analysis.
202014
18 202311
19 201510
20 20199

About André Panisson

André Panisson is a scholar working on Artificial Intelligence, Sociology and Political Science, Transportation, Computer Networks and Communications and Information Systems, having authored 48 papers that have together received 903 indexed citations. Recurring topics across this work include Misinformation and Its Impacts (9 papers), Human Mobility and Location-Based Analysis (8 papers), Explainable Artificial Intelligence (XAI) (7 papers), Advanced Graph Neural Networks (5 papers), Recommender Systems and Techniques (5 papers), Complex Network Analysis Techniques (5 papers), COVID-19 epidemiological studies (4 papers) and Vaccine Coverage and Hesitancy (4 papers). The work is most often cited by research in Computational Mathematics (33 citations), Transportation (140 citations), Statistical and Nonlinear Physics (226 citations), Health Informatics (22 citations) and Modeling and Simulation (58 citations). André Panisson has collaborated with scholars based in Italy, United States and France. Frequent co-authors include Ciro Cattuto, Laëtitia Gauvin, Michele Tizzoni, Daniela Paolotti, Alain Barrat, Michele Starnini, Paolo Bajardi, Michele Tizzani, Alan Perotti and Giancarlo Ruffo. Their work appears in journals such as EPJ Data Science, Journal of Medical Internet Research, Computer Graphics Forum, PLoS Computational Biology and IEEE Transactions on Knowledge and Data Engineering.

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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