Marcell Nagy
Impact in
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- Online Learning and Analytics
- Health Informatics top 10%
- Artificial Intelligence in Healthcare and Education
Papers in
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- Complex Network Analysis Techniques 14
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- Mental Health Research Topics 9
- Co-authors
- Roland Molontay (28 shared papers)Péter Tamás Kovács (1 shared paper)Imola Török (2 shared papers)Judit Bajor (2 shared papers)Ferenc Izbéki (2 shared papers)Gabriella Pár (2 shared papers)Péter Jenő Hegyi (2 shared papers)Szilárd Váncsa (2 shared papers)
In The Last Decade
Marcell Nagy
24 papers receiving 400 citations
Peers
Comparison fields: 5 of 86
- Computer Science Applications 171
- Health Informatics 21
- Health Information Management 31
- Statistical and Nonlinear Physics 53
- Artificial Intelligence 100
Countries citing papers authored by Marcell Nagy
This map shows the geographic impact of Marcell Nagy'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 Marcell Nagy with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marcell Nagy more than expected).
Fields of papers citing papers by Marcell Nagy
This network shows the impact of papers produced by Marcell Nagy. 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 Marcell Nagy. The network helps show where Marcell Nagy may publish in the future.
Co-authors
The 25 scholars most cited alongside Marcell Nagy, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 31 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2022 | 71 | |
| 2 | 2018 | 67 | |
| 3 | 2023 | 63 | |
| 4 | 2020 | 61 | |
| 5 | 2019 | 23 | |
| 6 | 2021 | 20 | |
| 7 | 2022 | 19 | |
| 8 | 2019 | 18 | |
| 9 | 2021 | 17 | |
| 10 | 2021 | 15 | |
| 11 | 2022 | 8 | |
| 12 | 2022 | 6 | |
| 13 | 2023 | 6 | |
| 14 | 2024 | 4 | |
| 15 | 2022 | 4 | |
| 16 | 2019 | 3 | |
| 17 | 2025 | 3 | |
| 18 | 2019 | 3 | |
| 19 | 2024 | 1 | |
| 20 | Data-driven Analysis of Complex Networks and their Model-generated Counterparts. | 2018 | 1 |
About Marcell Nagy
Marcell Nagy is a scholar working on Statistical and Nonlinear Physics, Experimental and Cognitive Psychology, Computer Science Applications, Health Informatics and Artificial Intelligence, having authored 31 papers that have together received 417 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (14 papers), Bioinformatics and Genomic Networks (9 papers), Mental Health Research Topics (9 papers), Online Learning and Analytics (6 papers), Artificial Intelligence in Healthcare and Education (3 papers), Theoretical and Computational Physics (3 papers), Higher Education Learning Practices (3 papers) and Hate Speech and Cyberbullying Detection (2 papers). The work is most often cited by research in Computer Science Applications (171 citations), Health Informatics (21 citations), Health Information Management (31 citations), Statistical and Nonlinear Physics (53 citations) and Artificial Intelligence (100 citations). Marcell Nagy has collaborated with scholars based in Hungary, Spain and Denmark. Frequent co-authors include Roland Molontay, Péter Tamás Kovács, Imola Török, Judit Bajor, Ferenc Izbéki, Gabriella Pár, Péter Jenő Hegyi, Szilárd Váncsa, Roland Hágendorn and Roland Fejes. Their work appears in journals such as Applied Network Science, Assessment & Evaluation in Higher Education, Scientific Reports, Fractals and Network Science.
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.