James Schaffer
Impact in
- Health Informatics top 5%
- Artificial Intelligence in Healthcare and Education
- General Decision Sciences top 10%
Papers in
-
- Data Visualization and Analytics 4
-
- Complex Network Analysis Techniques 4
- Co-authors
- John O’Donovan (15 shared papers)Tobias Höllerer (14 shared papers)Pigi Kouki (3 shared papers)Jay M. Pujara (3 shared papers)Lise Getoor (3 shared papers)James Michaelis (1 shared paper)Laura Ranee Marusich (5 shared papers)Cleotilde González (5 shared papers)
- Journals
- Network Science (1 paper)Human Factors The Journal of the Human Factors and Ergonomics Society (1 paper)International Journal of Human-Computer Studies (1 paper)ACM Transactions on Interactive Intelligent Systems (1 paper)Lecture notes in computer science (2 papers)
- Partner nations
- United States
In The Last Decade
James Schaffer
19 papers receiving 476 citations
Peers
Comparison fields: 5 of 65
- Health Informatics 41
- General Decision Sciences 20
- Safety Research 85
- Artificial Intelligence 272
- Information Systems 163
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 | 129 | |
| 2 | 2019 | 91 | |
| 3 | 2016 | 53 | |
| 4 | 2017 | 53 | |
| 5 | 2020 | 35 | |
| 6 | 2015 | 29 | |
| 7 | Hypothetical Recommendation: A Study of Interactive Profile Manipulation Behavior for Recommender Systems | 2015 | 22 |
| 8 | 2019 | 16 | |
| 9 | 2014 | 13 | |
| 10 | 2019 | 13 | |
| 11 | 2018 | 8 | |
| 12 | 2016 | 6 | |
| 13 | 2019 | 6 | |
| 14 | 2018 | 4 | |
| 15 | 2014 | 4 | |
| 16 | 2013 | 3 | |
| 17 | 2020 | 3 | |
| 18 | 2018 | 2 | |
| 19 | 2014 | 1 |
About James Schaffer
James Schaffer is a scholar working on Computer Vision and Pattern Recognition, Statistical and Nonlinear Physics, Information Systems and Management, Artificial Intelligence and General Decision Sciences, having authored 19 papers that have together received 491 indexed citations. Recurring topics across this work include Data Visualization and Analytics (4 papers), Recommender Systems and Techniques (4 papers), Complex Network Analysis Techniques (4 papers), AI-based Problem Solving and Planning (2 papers), Decision-Making and Behavioral Economics (2 papers), Advanced Bandit Algorithms Research (2 papers), Personal Information Management and User Behavior (2 papers) and Experimental Behavioral Economics Studies (2 papers). The work is most often cited by research in Health Informatics (41 citations), General Decision Sciences (20 citations), Safety Research (85 citations), Artificial Intelligence (272 citations) and Information Systems (163 citations). James Schaffer has collaborated with scholars based in United States. Frequent co-authors include John O’Donovan, Tobias Höllerer, Pigi Kouki, Jay M. Pujara, Lise Getoor, James Michaelis, Laura Ranee Marusich, Cleotilde González, Michael S. Yu and Emrah Onal. Their work appears in journals such as Network Science, Human Factors The Journal of the Human Factors and Ergonomics Society, International Journal of Human-Computer Studies, ACM Transactions on Interactive Intelligent Systems and Lecture notes in computer science.
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.