Nina McMurry
About
In The Last Decade
Nina McMurry
6 papers receiving 127 citations
Peers
Comparison fields: 5 of 51
- Information Systems 87
- Sociology and Political Science 85
- Modeling and Simulation 23
- General Health Professions 20
- Artificial Intelligence 15
Countries citing papers authored by Nina McMurry
This map shows the geographic impact of Nina McMurry'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 Nina McMurry with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nina McMurry more than expected).
Fields of papers citing papers by Nina McMurry
This network shows the impact of papers produced by Nina McMurry. 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 Nina McMurry. The network helps show where Nina McMurry may publish in the future.
Co-authorship network of co-authors of Nina McMurry
This figure shows the co-authorship network connecting the top 25 collaborators of Nina McMurry. A scholar is included among the top collaborators of Nina McMurry based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Nina McMurry. Nina McMurry is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 12 | |
| 3 | 5 | |
| 4 | 23 | |
| 5 | 85 | |
| 6 | 3 | |
| 7 | 1 |
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.