Dániel Ábel
Impact in
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- Complex Network Analysis Techniques
- Opinion Dynamics and Social Influence
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- Mental Health Research Topics
Papers in
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- Complex Network Analysis Techniques 3
- Opinion Dynamics and Social Influence 2
- Co-authors
- Tamás Vicsek (6 shared papers)Gergely Palla (2 shared papers)Illés J. Farkas (2 shared papers)Alpár S. Lázár (1 shared paper)Gábor Vásárhelyi (2 shared papers)Máté Nagy (2 shared papers)Csaba Virágh (1 shared paper)Norbert Tarcai (1 shared paper)
- Journals
- Physica A Statistical Mechanics and its Applications (2 papers)Scientific Reports (1 paper)New Journal of Physics (1 paper)Europhysics Letters (EPL) (1 paper)Nano Letters (1 paper)
- Partner nations
- HungaryUnited KingdomUnited States
In The Last Decade
Dániel Ábel
8 papers receiving 287 citations
Peers
Comparison fields: 5 of 72
- Statistical and Nonlinear Physics 170
- Experimental and Cognitive Psychology 39
- Computer Networks and Communications 63
- Biological Psychiatry 6
- Artificial Intelligence 60
Countries citing papers authored by Dániel Ábel
This map shows the geographic impact of Dániel Ábel'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 Dániel Ábel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dániel Ábel more than expected).
Fields of papers citing papers by Dániel Ábel
This network shows the impact of papers produced by Dániel Ábel. 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 Dániel Ábel. The network helps show where Dániel Ábel may publish in the future.
Co-authors
The 25 scholars most cited alongside Dániel Ábel, 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 | 2007 | 164 | |
| 2 | 2010 | 56 | |
| 3 | 2019 | 33 | |
| 4 | 2011 | 23 | |
| 5 | 2008 | 8 | |
| 6 | 2011 | 7 | |
| 7 | 2024 | 2 | |
| 8 | 2019 | 1 |
About Dániel Ábel
Dániel Ábel is a scholar working on Statistical and Nonlinear Physics, Computer Networks and Communications, Molecular Biology, Condensed Matter Physics and Artificial Intelligence, having authored 8 papers that have together received 294 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (3 papers), Advanced Clustering Algorithms Research (2 papers), Opinion Dynamics and Social Influence (2 papers), Diffusion and Search Dynamics (2 papers), Quantum and electron transport phenomena (1 paper), Physics of Superconductivity and Magnetism (1 paper), Graph theory and applications (1 paper) and Insect and Arachnid Ecology and Behavior (1 paper). The work is most often cited by research in Statistical and Nonlinear Physics (170 citations), Experimental and Cognitive Psychology (39 citations), Computer Networks and Communications (63 citations), Biological Psychiatry (6 citations) and Artificial Intelligence (60 citations). Dániel Ábel has collaborated with scholars based in Hungary, United Kingdom and United States. Frequent co-authors include Tamás Vicsek, Gergely Palla, Illés J. Farkas, Alpár S. Lázár, Gábor Vásárhelyi, Máté Nagy, Csaba Virágh, Norbert Tarcai, Péter L. Várkonyi and Sara Martí‐Sánchez. Their work appears in journals such as Physica A Statistical Mechanics and its Applications, Scientific Reports, New Journal of Physics, Europhysics Letters (EPL) and Nano Letters.
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.