Stuart Mcilroy
Impact in
- Information Systems top 5%
- Software Engineering Research
- Software Engineering Techniques and Practices
- Web Data Mining and Analysis
- Mobile and Web Applications
- Software top 10%
Papers in
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- Digital Marketing and Social Media 4
-
- Web Data Mining and Analysis 3
- Spam and Phishing Detection 1
- Software Engineering Research 1
- Co-authors
- Nasir Ali (4 shared papers)Ahmed E. Hassan (4 shared papers)Hammad Khalid (1 shared paper)Weiyi Shang (2 shared papers)Jiaping Gui (1 shared paper)William G. J. Halfond (1 shared paper)Meiyappan Nagappan (1 shared paper)Thomas Trappenberg (1 shared paper)
- Journals
- Empirical Software Engineering (2 papers)IEEE Software (1 paper)Communications of the ACM (1 paper)QSpace (Queen's University Library) (1 paper)2015 IEEE/ACM 37th IEEE International Conference on Software Engineering (1 paper)
- Partner nations
- CanadaUnited States
In The Last Decade
Stuart Mcilroy
7 papers receiving 350 citations
Peers
Comparison fields: 5 of 58
- Information Systems 234
- Software 34
- Computer Science Applications 46
- Signal Processing 78
- Information Systems and Management 40
Countries citing papers authored by Stuart Mcilroy
This map shows the geographic impact of Stuart Mcilroy'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 Stuart Mcilroy with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stuart Mcilroy more than expected).
Fields of papers citing papers by Stuart Mcilroy
This network shows the impact of papers produced by Stuart Mcilroy. 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 Stuart Mcilroy. The network helps show where Stuart Mcilroy may publish in the future.
Co-authors
The 10 scholars most cited alongside Stuart Mcilroy, 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 | 2015 | 133 | |
| 2 | 2015 | 126 | |
| 3 | 2015 | 35 | |
| 4 | 2015 | 35 | |
| 5 | 2017 | 28 | |
| 6 | 2017 | 2 | |
| 7 | Empirical Studies of the Distribution and Feedback Mechanisms of Mobile App Stores | 2014 | 1 |
About Stuart Mcilroy
Stuart Mcilroy is a scholar working on Sociology and Political Science, Information Systems, Electrical and Electronic Engineering, Strategy and Management and Computer Networks and Communications, having authored 7 papers that have together received 360 indexed citations. Recurring topics across this work include Digital Marketing and Social Media (4 papers), Green IT and Sustainability (3 papers), Web Data Mining and Analysis (3 papers), Digital Platforms and Economics (2 papers), Digital Imaging for Blood Diseases (1 paper), Spam and Phishing Detection (1 paper), Caching and Content Delivery (1 paper) and Software Engineering Research (1 paper). The work is most often cited by research in Information Systems (234 citations), Software (34 citations), Computer Science Applications (46 citations), Signal Processing (78 citations) and Information Systems and Management (40 citations). Stuart Mcilroy has collaborated with scholars based in Canada and United States. Frequent co-authors include Nasir Ali, Ahmed E. Hassan, Hammad Khalid, Weiyi Shang, Jiaping Gui, William G. J. Halfond, Meiyappan Nagappan, Thomas Trappenberg, James Thomas Toguri and Christine Lehmann. Their work appears in journals such as Empirical Software Engineering, IEEE Software, Communications of the ACM, QSpace (Queen's University Library) and 2015 IEEE/ACM 37th IEEE International Conference on Software Engineering.
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.