Steven Burrows
Impact in
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- Online Learning and Analytics
- Artificial Intelligence top 5%
- Topic Modeling
- Natural Language Processing Techniques
- Authorship Attribution and Profiling
- Intelligent Tutoring Systems and Adaptive Learning
Papers in
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- Topic Modeling 7
- Authorship Attribution and Profiling 3
- Imbalanced Data Classification Techniques 1
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- Software Engineering Research 3
- Educational Technology and Assessment 2
- Co-authors
- Benno Stein (6 shared papers)Iryna Gurevych (1 shared paper)Tim Gollub (3 shared papers)S. M. M. Tahaghoghi (1 shared paper)Justin Zobel (1 shared paper)Martin Potthast (1 shared paper)Andrew Turpin (2 shared papers)Alexandra L. Uitdenbogerd (2 shared papers)
In The Last Decade
Steven Burrows
13 papers receiving 491 citations
Peers
Comparison fields: 5 of 60
- Computer Science Applications 88
- Artificial Intelligence 394
- Health Informatics 13
- Information Systems 224
- Signal Processing 71
Countries citing papers authored by Steven Burrows
This map shows the geographic impact of Steven Burrows'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 Steven Burrows with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Steven Burrows more than expected).
Fields of papers citing papers by Steven Burrows
This network shows the impact of papers produced by Steven Burrows. 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 Steven Burrows. The network helps show where Steven Burrows may publish in the future.
Co-authors
The 9 scholars most cited alongside Steven Burrows, 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 | 2014 | 273 | |
| 2 | 2006 | 61 | |
| 3 | 2013 | 56 | |
| 4 | 2012 | 43 | |
| 5 | 2012 | 39 | |
| 6 | 2011 | 18 | |
| 7 | 2012 | 18 | |
| 8 | 2011 | 16 | |
| 9 | Simulation data mining for supporting bridge design | 2011 | 8 |
| 10 | 2009 | 8 | |
| 11 | 2009 | 8 | |
| 12 | Searching the MEDLARS file on NLM and BRS a comparative study. | 1979 | 7 |
| 13 | First Experiences with TIRA for Reproducible Evaluation in Information Retrieval. | 2012 | 3 |
About Steven Burrows
Steven Burrows is a scholar working on Artificial Intelligence, Information Systems, Computer Science Applications, Safety Research and Education, having authored 13 papers that have together received 558 indexed citations. Recurring topics across this work include Topic Modeling (7 papers), Authorship Attribution and Profiling (3 papers), Software Engineering Research (3 papers), Mobile Crowdsensing and Crowdsourcing (3 papers), Academic integrity and plagiarism (2 papers), Educational Technology and Assessment (2 papers), Student Assessment and Feedback (2 papers) and Imbalanced Data Classification Techniques (1 paper). The work is most often cited by research in Computer Science Applications (88 citations), Artificial Intelligence (394 citations), Health Informatics (13 citations), Information Systems (224 citations) and Signal Processing (71 citations). Steven Burrows has collaborated with scholars based in Germany and Australia. Frequent co-authors include Benno Stein, Iryna Gurevych, Tim Gollub, S. M. M. Tahaghoghi, Justin Zobel, Martin Potthast, Andrew Turpin, Alexandra L. Uitdenbogerd and Mark R. Shortis. Their work appears in journals such as Software Practice and Experience, International Journal of Artificial Intelligence in Education, Australasian Journal of Educational Technology, ACM Transactions on Intelligent Systems and Technology and PubMed.
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.