James Schaffer
Impact in
- Health Informatics top 5%
- Artificial Intelligence in Healthcare and Education
Papers in
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- Advanced Text Analysis Techniques 2
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- Data Visualization and Analytics 3
- Co-authors
- John O’Donovan (14 shared papers)Tobias Höllerer (12 shared papers)Jay Pujara (3 shared papers)Lise Getoor (3 shared papers)Pigi Kouki (3 shared papers)James Michaelis (1 shared paper)Laura R. Marusich (4 shared papers)Cleotilde González (4 shared papers)
- Journals
- Network Science (1 paper)International Journal of Human-Computer Studies (1 paper)ACM Transactions on Interactive Intelligent Systems (1 paper)Human Factors The Journal of the Human Factors and Ergonomics Society (1 paper)Civil War Book Review (1 paper)
- Partner nations
- United States
In The Last Decade
James Schaffer
16 papers receiving 401 citations
Peers
Comparison fields: 5 of 61
- Health Informatics 35
- General Decision Sciences 17
- Safety Research 75
- Artificial Intelligence 238
- Information Systems 138
Countries citing papers authored by James Schaffer
This map shows the geographic impact of James Schaffer'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 James Schaffer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites James Schaffer more than expected).
Fields of papers citing papers by James Schaffer
This network shows the impact of papers produced by James Schaffer. 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 James Schaffer. The network helps show where James Schaffer may publish in the future.
Co-authors
The 25 scholars most cited alongside James Schaffer, 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 | 2019 | 102 | |
| 2 | 2019 | 82 | |
| 3 | 2017 | 51 | |
| 4 | 2016 | 44 | |
| 5 | 2020 | 30 | |
| 6 | 2015 | 28 | |
| 7 | Hypothetical Recommendation: A Study of Interactive Profile Manipulation Behavior for Recommender Systems | 2015 | 17 |
| 8 | 2019 | 14 | |
| 9 | 2019 | 12 | |
| 10 | 2014 | 11 | |
| 11 | 2018 | 8 | |
| 12 | 2016 | 6 | |
| 13 | 2019 | 6 | |
| 14 | 2014 | 4 | |
| 15 | 2013 | 3 | |
| 16 | 2018 | 2 |
About James Schaffer
James Schaffer is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems, Statistical and Nonlinear Physics and Social Psychology, having authored 16 papers that have together received 420 indexed citations. Recurring topics across this work include Recommender Systems and Techniques (4 papers), Complex Network Analysis Techniques (4 papers), Data Visualization and Analytics (3 papers), Experimental Behavioral Economics Studies (2 papers), Human-Automation Interaction and Safety (2 papers), Misinformation and Its Impacts (2 papers), Advanced Text Analysis Techniques (2 papers) and Decision-Making and Behavioral Economics (2 papers). The work is most often cited by research in Health Informatics (35 citations), General Decision Sciences (17 citations), Safety Research (75 citations), Artificial Intelligence (238 citations) and Information Systems (138 citations). James Schaffer has collaborated with scholars based in United States. Frequent co-authors include John O’Donovan, Tobias Höllerer, Jay Pujara, Lise Getoor, Pigi Kouki, James Michaelis, Laura R. Marusich, Cleotilde González, Michael Yu and Jonathan Z. Bakdash. Their work appears in journals such as Network Science, International Journal of Human-Computer Studies, ACM Transactions on Interactive Intelligent Systems, Human Factors The Journal of the Human Factors and Ergonomics Society and Civil War Book Review.
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.