Nathan Self
Impact in
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- Stock Market Forecasting Methods
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- Complex Network Analysis Techniques
- Opinion Dynamics and Social Influence
Papers in
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- Anomaly Detection Techniques and Applications 5
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- Complex Network Analysis Techniques 5
- Opinion Dynamics and Social Influence 4
- Co-authors
- Naren Ramakrishnan (23 shared papers)Fang Jin (3 shared papers)Chang‐Tien Lu (10 shared papers)Parang Saraf (7 shared papers)P. J. Butler (3 shared papers)Wei Wang (1 shared paper)Feng Chen (2 shared papers)Zhiqian Chen (6 shared papers)
- Journals
- PLoS ONE (2 papers)Big Data (1 paper)Social Network Analysis and Mining (1 paper)Information Visualization (1 paper)ACM Transactions on Intelligent Systems and Technology (1 paper)
- Partner nations
- United StatesEcuadorUnited Kingdom
In The Last Decade
Nathan Self
23 papers receiving 216 citations
Peers
Comparison fields: 5 of 61
- Management Science and Operations Research 53
- Statistical and Nonlinear Physics 44
- Artificial Intelligence 84
- Signal Processing 27
- Transportation 13
Countries citing papers authored by Nathan Self
This map shows the geographic impact of Nathan Self'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 Nathan Self with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nathan Self more than expected).
Fields of papers citing papers by Nathan Self
This network shows the impact of papers produced by Nathan Self. 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 Nathan Self. The network helps show where Nathan Self may publish in the future.
Co-authors
The 25 scholars most cited alongside Nathan Self, 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 25 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2013 | 37 | |
| 2 | 2017 | 25 | |
| 3 | 2014 | 23 | |
| 4 | 2016 | 20 | |
| 5 | 2018 | 17 | |
| 6 | 2020 | 16 | |
| 7 | 2014 | 16 | |
| 8 | 2020 | 11 | |
| 9 | 2019 | 8 | |
| 10 | 2018 | 8 | |
| 11 | 2019 | 7 | |
| 12 | 2020 | 5 | |
| 13 | 2019 | 5 | |
| 14 | 2019 | 5 | |
| 15 | Bringing interactive visual analytics to the classroom for developing EDA skills | 2018 | 4 |
| 16 | 2023 | 4 | |
| 17 | 2024 | 3 | |
| 18 | 2018 | 3 | |
| 19 | 2019 | 3 | |
| 20 | 2020 | 2 |
About Nathan Self
Nathan Self is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics, Computer Vision and Pattern Recognition, Management Science and Operations Research and Signal Processing, having authored 25 papers that have together received 227 indexed citations. Recurring topics across this work include Anomaly Detection Techniques and Applications (5 papers), Complex Network Analysis Techniques (5 papers), Data Visualization and Analytics (4 papers), Opinion Dynamics and Social Influence (4 papers), Data Management and Algorithms (3 papers), Data-Driven Disease Surveillance (3 papers), Machine Learning in Materials Science (3 papers) and ICT in Developing Communities (2 papers). The work is most often cited by research in Management Science and Operations Research (53 citations), Statistical and Nonlinear Physics (44 citations), Artificial Intelligence (84 citations), Signal Processing (27 citations) and Transportation (13 citations). Nathan Self has collaborated with scholars based in United States, Ecuador and United Kingdom. Frequent co-authors include Naren Ramakrishnan, Fang Jin, Chang‐Tien Lu, Parang Saraf, P. J. Butler, Wei Wang, Feng Chen, Zhiqian Chen, Rupinder Paul Khandpur and Kaiqun Fu. Their work appears in journals such as PLoS ONE, Big Data, Social Network Analysis and Mining, Information Visualization and ACM Transactions on Intelligent Systems and Technology.
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.