Séverine Affeldt
Impact in
- Marketing top 10%
- Customer churn and segmentation
- Consumer Retail Behavior Studies
Papers in
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- Advanced Clustering Algorithms Research 2
- Bayesian Modeling and Causal Inference 2
- Text and Document Classification Technologies 2
-
- Gene expression and cancer classification 1
- Co-authors
- Mohamed Nadif (6 shared papers)Hervé Isambert (6 shared papers)Param Priya Singh (3 shared papers)Jacques Camonis (2 shared papers)Ilaria Cascone (2 shared papers)Lazhar Labiod (3 shared papers)Nataliya Sokolovska (2 shared papers)Edi Prifti (2 shared papers)
- Journals
- BMC Bioinformatics (2 papers)Statistics and Computing (1 paper)Cell Reports (1 paper)Frontiers in Physiology (1 paper)PLoS Computational Biology (1 paper)
- Partner nations
- FranceUnited KingdomBelgium
In The Last Decade
Séverine Affeldt
13 papers receiving 197 citations
Peers
Comparison fields: 5 of 71
- Computational Mathematics 3
- Marketing 44
- Organizational Behavior and Human Resource Management 16
- Artificial Intelligence 50
- Molecular Biology 78
Countries citing papers authored by Séverine Affeldt
This map shows the geographic impact of Séverine Affeldt'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 Séverine Affeldt with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Séverine Affeldt more than expected).
Fields of papers citing papers by Séverine Affeldt
This network shows the impact of papers produced by Séverine Affeldt. 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 Séverine Affeldt. The network helps show where Séverine Affeldt may publish in the future.
Co-authors
The 25 scholars most cited alongside Séverine Affeldt, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2022 | 39 | |
| 2 | 2012 | 38 | |
| 3 | 2019 | 32 | |
| 4 | 2017 | 26 | |
| 5 | 2016 | 20 | |
| 6 | 2022 | 12 | |
| 7 | 2017 | 10 | |
| 8 | 2021 | 10 | |
| 9 | 2016 | 6 | |
| 10 | Robust reconstruction of causal graphical models based on conditional 2-point and 3-point information | 2015 | 4 |
| 11 | 2021 | 4 | |
| 12 | 2022 | 1 | |
| 13 | 2013 | 1 | |
| 14 | 2024 | 0 |
About Séverine Affeldt
Séverine Affeldt is a scholar working on Artificial Intelligence, Molecular Biology, Statistical and Nonlinear Physics, Marketing and Endocrinology, Diabetes and Metabolism, having authored 14 papers that have together received 203 indexed citations. Recurring topics across this work include Advanced Clustering Algorithms Research (2 papers), Bayesian Modeling and Causal Inference (2 papers), Complex Network Analysis Techniques (2 papers), Text and Document Classification Technologies (2 papers), Customer churn and segmentation (2 papers), Consumer Market Behavior and Pricing (1 paper), Cancer Genomics and Diagnostics (1 paper) and Gene expression and cancer classification (1 paper). The work is most often cited by research in Computational Mathematics (3 citations), Marketing (44 citations), Organizational Behavior and Human Resource Management (16 citations), Artificial Intelligence (50 citations) and Molecular Biology (78 citations). Séverine Affeldt has collaborated with scholars based in France, United Kingdom and Belgium. Frequent co-authors include Mohamed Nadif, Hervé Isambert, Param Priya Singh, Jacques Camonis, Ilaria Cascone, Lazhar Labiod, Nataliya Sokolovska, Edi Prifti, Jean‐Daniel Zucker and Eric O. Verger. Their work appears in journals such as BMC Bioinformatics, Statistics and Computing, Cell Reports, Frontiers in Physiology and PLoS Computational Biology.
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.