Misha Teplitskiy
- Statistics, Probability and Uncertainty top 2%
- Sociology and Political Science
- Communication top 10%
- Information Systems and Management top 10%
- Information Systems
- Co-authors
- Eamon DuedeKarim R. LakhaniMichael MeniettiJames A. EvansKonrad P. KördingDaniel E. AcuñaJohn Levi MartinHao Peng
- Topics
- scientometrics and bibliometrics research (11 papers)Meta-analysis and systematic reviews (4 papers)Management and Organizational Studies (3 papers)
- Partner nations
- United StatesItalyPhilippines
In The Last Decade
Misha Teplitskiy
22 papers receiving 302 citations
Peers
Comparison fields: 5 of 88
- Statistics, Probability and Uncertainty 128
- Sociology and Political Science 73
- Communication 50
- Information Systems and Management 50
- Information Systems 41
Countries citing papers authored by Misha Teplitskiy
This map shows the geographic impact of Misha Teplitskiy'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 Misha Teplitskiy with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Misha Teplitskiy more than expected).
Fields of papers citing papers by Misha Teplitskiy
This network shows the impact of papers produced by Misha Teplitskiy. 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 Misha Teplitskiy. The network helps show where Misha Teplitskiy may publish in the future.
Co-authorship network of co-authors of Misha Teplitskiy
This figure shows the co-authorship network connecting the top 25 collaborators of Misha Teplitskiy. A scholar is included among the top collaborators of Misha Teplitskiy 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 Misha Teplitskiy. Misha Teplitskiy 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 | 2 | |
| 3 | 0 | |
| 4 | 1 | |
| 5 | 3 | |
| 6 | 6 | |
| 7 | 6 | |
| 8 | 2 | |
| 9 | 4 | |
| 10 | 1 | |
| 11 | 2 | |
| 12 | 21 | |
| 13 | 3 | |
| 14 | Why (almost) Everything We Know About Citations is Wrong: Evidence from Authors | 6 |
| 15 | 69 | |
| 16 | 3 | |
| 17 | 63 | |
| 18 | 20 | |
| 19 | 18 | |
| 20 | 5 |
About Misha Teplitskiy
Misha Teplitskiy is a scholar working on Statistics, Probability and Uncertainty, Health Informatics and Information Systems and Management, having authored 23 papers that have together received 318 indexed citations. Recurring topics across this work include scientometrics and bibliometrics research (11 papers), Meta-analysis and systematic reviews (4 papers) and Management and Organizational Studies (3 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (128 citations), Information Systems and Management (50 citations) and Communication (50 citations). Misha Teplitskiy has collaborated with scholars based in United States, Italy and Philippines. Frequent co-authors include Eamon Duede, Karim R. Lakhani, Michael Menietti, James A. Evans, Konrad P. Körding, Daniel E. Acuña, John Levi Martin, Hao Peng, Eva C. Guinan and G. Kenneth Gray. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nature Communications and PLoS ONE.
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.