Jason Tsay
Impact in
- Computer Science Applications top 0.2%
- Open Source Software Innovations
- Mobile Crowdsensing and Crowdsourcing
- Information Systems top 0.5%
- Software Engineering Research
- Software Engineering Techniques and Practices
Papers in
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- Software Engineering Research 10
- Software Engineering Techniques and Practices 3
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- Open Source Software Innovations 6
- Co-authors
- Laura Dabbish (6 shared papers)Jim Herbsleb (1 shared paper)James D. Herbsleb (5 shared papers)Dakuo Wang (1 shared paper)Q. Vera Liao (1 shared paper)Casey Dugan (1 shared paper)Michael Müller (1 shared paper)Thomas Erickson (1 shared paper)
- Journals
- IEEE Software (1 paper)Empirical Software Engineering (1 paper)Research Showcase @ Carnegie Mellon University (Carnegie Mellon University) (1 paper)Journal of Polymer Science Polymer Letters Edition (1 paper)Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (1 paper)
- Partner nations
- United StatesBrazil
In The Last Decade
Jason Tsay
15 papers receiving 1.3k citations
Jason Tsay's Hit Papers
Peers
Comparison fields: 5 of 109
- Computer Science Applications 744
- Information Systems 937
- Communication 259
- Information Systems and Management 187
- Software 86
Countries citing papers authored by Jason Tsay
This map shows the geographic impact of Jason Tsay'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 Jason Tsay with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jason Tsay more than expected).
Fields of papers citing papers by Jason Tsay
This network shows the impact of papers produced by Jason Tsay. 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 Jason Tsay. The network helps show where Jason Tsay may publish in the future.
Co-authors
The 18 scholars most cited alongside Jason Tsay, 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 | Social coding in GitHub Hit paper breakdown → | 2012 | 655 |
| 2 | Influence of social and technical factors for evaluating contribution in GitHub Hit paper breakdown → | 2014 | 273 |
| 3 | 2019 | 162 | |
| 4 | 2014 | 134 | |
| 5 | 2012 | 61 | |
| 6 | 2012 | 26 | |
| 7 | 1984 | 15 | |
| 8 | 2021 | 13 | |
| 9 | 2020 | 12 | |
| 10 | 2013 | 10 | |
| 11 | 2011 | 6 | |
| 12 | 2022 | 6 | |
| 13 | 2024 | 5 | |
| 14 | 2022 | 3 | |
| 15 | 2017 | 1 |
About Jason Tsay
Jason Tsay is a scholar working on Information Systems, Computer Science Applications, Artificial Intelligence, Communication and Information Systems and Management, having authored 15 papers that have together received 1.4k indexed citations. Recurring topics across this work include Software Engineering Research (10 papers), Open Source Software Innovations (6 papers), Machine Learning and Data Classification (4 papers), Scientific Computing and Data Management (4 papers), Knowledge Management and Sharing (3 papers), Software Testing and Debugging Techniques (3 papers), Software Engineering Techniques and Practices (3 papers) and Wikis in Education and Collaboration (3 papers). The work is most often cited by research in Computer Science Applications (744 citations), Information Systems (937 citations), Communication (259 citations), Information Systems and Management (187 citations) and Software (86 citations). Jason Tsay has collaborated with scholars based in United States and Brazil. Frequent co-authors include Laura Dabbish, Jim Herbsleb, James D. Herbsleb, Dakuo Wang, Q. Vera Liao, Casey Dugan, Michael Müller, Thomas Erickson, David Piorkowski and Martin Hirzel. Their work appears in journals such as IEEE Software, Empirical Software Engineering, Research Showcase @ Carnegie Mellon University (Carnegie Mellon University), Journal of Polymer Science Polymer Letters Edition and Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining.
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.