Nathan Bartley
Impact in
- Artificial Intelligence top 5%
- Machine Learning and Data Classification
- Evolutionary Algorithms and Applications
- Hate Speech and Cyberbullying Detection
- Information Systems top 10%
- Cybercrime and Law Enforcement Studies
Papers in
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- Ethics and Social Impacts of AI 3
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- Recommender Systems and Techniques 3
- Cybercrime and Law Enforcement Studies 1
- Co-authors
- Randal S. Olson (1 shared paper)Ryan J. Urbanowicz (1 shared paper)Jason H. Moore (1 shared paper)Emilio Ferrara (3 shared papers)Kristina Lerman (5 shared papers)Andrés Abeliuk (2 shared papers)Sandeep Soni (1 shared paper)Nazgol Tavabi (1 shared paper)
- Journals
- Internet Research (1 paper)Lecture notes in computer science (1 paper)Communications in computer and information science (1 paper)IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) (1 paper)Genetic and Evolutionary Computation Conference (GECCO) (1 paper)
- Partner nations
- United StatesChile
In The Last Decade
Nathan Bartley
6 papers receiving 526 citations
Nathan Bartley's Hit Papers
Peers
Comparison fields: 5 of 103
- Artificial Intelligence 239
- Information Systems 67
- Signal Processing 16
- Health Information Management 15
- Computer Science Applications 9
Countries citing papers authored by Nathan Bartley
This map shows the geographic impact of Nathan Bartley'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 Bartley with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nathan Bartley more than expected).
Fields of papers citing papers by Nathan Bartley
This network shows the impact of papers produced by Nathan Bartley. 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 Bartley. The network helps show where Nathan Bartley may publish in the future.
Co-authors
The 13 scholars most cited alongside Nathan Bartley, 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 | Evaluation of a Tree-based Pipeline Optimization Tool for Automating Data Science Hit paper breakdown → | 2016 | 447 |
| 2 | 2019 | 36 | |
| 3 | 2021 | 33 | |
| 4 | 2019 | 20 | |
| 5 | 2022 | 5 | |
| 6 | 2023 | 2 | |
| 7 | 2024 | 0 | |
| 8 | 2025 | 0 |
About Nathan Bartley
Nathan Bartley is a scholar working on Safety Research, Information Systems, Statistical and Nonlinear Physics, Communication and Sociology and Political Science, having authored 8 papers that have together received 543 indexed citations. Recurring topics across this work include Ethics and Social Impacts of AI (3 papers), Recommender Systems and Techniques (3 papers), Complex Network Analysis Techniques (2 papers), Misinformation and Its Impacts (2 papers), Team Dynamics and Performance (1 paper), Hate Speech and Cyberbullying Detection (1 paper), Social Capital and Networks (1 paper) and Cybercrime and Law Enforcement Studies (1 paper). The work is most often cited by research in Artificial Intelligence (239 citations), Information Systems (67 citations), Signal Processing (16 citations), Health Information Management (15 citations) and Computer Science Applications (9 citations). Nathan Bartley has collaborated with scholars based in United States and Chile. Frequent co-authors include Randal S. Olson, Ryan J. Urbanowicz, Jason H. Moore, Emilio Ferrara, Kristina Lerman, Andrés Abeliuk, Sandeep Soni, Nazgol Tavabi, Yan Shen and Homa Hosseinmardi. Their work appears in journals such as Internet Research, Lecture notes in computer science, Communications in computer and information science, IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) and Genetic and Evolutionary Computation Conference (GECCO).
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.