Geoff Musick
Impact in
- Health Informatics top 10%
- Artificial Intelligence in Healthcare and Education
- Safety Research top 5%
- Ethics and Social Impacts of AI
Papers in
-
- Team Dynamics and Performance 5
- Human-Automation Interaction and Safety 4
-
- Privacy, Security, and Data Protection 2
- Digital Games and Media 2
- Co-authors
- Nathan J. McNeese (10 shared papers)Guo Freeman (3 shared papers)Beau G. Schelble (3 shared papers)Tom O’Neill (2 shared papers)Christopher Flathmann (5 shared papers)Rui Zhang (1 shared paper)Guo Freeman (1 shared paper)Bart P. Knijnenburg (5 shared papers)
- Journals
- Proceedings of the ACM on Human-Computer Interaction (6 papers)Computers in Human Behavior (1 paper)User Modeling and User-Adapted Interaction (1 paper)International Journal of Human-Computer Interaction (1 paper)ACM Transactions on Interactive Intelligent Systems (1 paper)
- Partner nations
- United StatesNetherlandsCanada
In The Last Decade
Geoff Musick
10 papers receiving 270 citations
Peers
Comparison fields: 5 of 51
- Health Informatics 20
- Safety Research 86
- Social Psychology 121
- Human-Computer Interaction 20
- Computer Science Applications 17
Countries citing papers authored by Geoff Musick
This map shows the geographic impact of Geoff Musick'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 Geoff Musick with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Geoff Musick more than expected).
Fields of papers citing papers by Geoff Musick
This network shows the impact of papers produced by Geoff Musick. 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 Geoff Musick. The network helps show where Geoff Musick may publish in the future.
Co-authors
The 12 scholars most cited alongside Geoff Musick, 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 | 2021 | 127 | |
| 2 | 2021 | 58 | |
| 3 | 2021 | 25 | |
| 4 | 2021 | 24 | |
| 5 | 2023 | 16 | |
| 6 | 2022 | 13 | |
| 7 | 2023 | 5 | |
| 8 | 2024 | 2 | |
| 9 | 2020 | 2 | |
| 10 | 2023 | 1 | |
| 11 | 2023 | 1 |
About Geoff Musick
Geoff Musick is a scholar working on Social Psychology, Sociology and Political Science, Information Systems and Management, Artificial Intelligence and Communication, having authored 11 papers that have together received 274 indexed citations. Recurring topics across this work include Team Dynamics and Performance (5 papers), Human-Automation Interaction and Safety (4 papers), Knowledge Management and Sharing (2 papers), Privacy, Security, and Data Protection (2 papers), Technology Adoption and User Behaviour (2 papers), Ethics and Social Impacts of AI (2 papers), Digital Games and Media (2 papers) and Explainable Artificial Intelligence (XAI) (1 paper). The work is most often cited by research in Health Informatics (20 citations), Safety Research (86 citations), Social Psychology (121 citations), Human-Computer Interaction (20 citations) and Computer Science Applications (17 citations). Geoff Musick has collaborated with scholars based in United States, Netherlands and Canada. Frequent co-authors include Nathan J. McNeese, Guo Freeman, Beau G. Schelble, Tom O’Neill, Christopher Flathmann, Rui Zhang, Guo Freeman, Bart P. Knijnenburg, Wen Duan and Nava Tintarev. Their work appears in journals such as Proceedings of the ACM on Human-Computer Interaction, Computers in Human Behavior, User Modeling and User-Adapted Interaction, International Journal of Human-Computer Interaction and ACM Transactions on Interactive Intelligent Systems.
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.