Marc Höglinger
Impact in
- Statistics and Probability top 5%
- Survey Sampling and Estimation Techniques
- Modeling and Simulation top 10%
- COVID-19 epidemiological studies
Papers in ⓘ
-
- COVID-19 and Mental Health 6
- Co-authors
- Ben Jann (3 shared papers)Andreas Diekmann (3 shared papers)André Moser (7 shared papers)Viktor von Wyl (6 shared papers)Milo A. Puhan (3 shared papers)Tala Ballouz (2 shared papers)Dominik Menges (2 shared papers)Marco Kaufmann (1 shared paper)
- Journals
- PLoS ONE (4 papers)JMIR Public Health and Surveillance (3 papers)Swiss Medical Weekly (2 papers)The European Journal of Health Economics (1 paper)Telemedicine Journal and e-Health (1 paper)
- Partner nations
- SwitzerlandGermanyCanada
In The Last Decade
Marc Höglinger
21 papers receiving 293 citations
Peers
Comparison fields: 5 of 79
- Statistics and Probability 99
- Modeling and Simulation 31
- Information Systems 85
- Sociology and Political Science 128
- Health 22
Countries citing papers authored by Marc Höglinger
This map shows the geographic impact of Marc Höglinger'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 Marc Höglinger with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marc Höglinger more than expected).
Fields of papers citing papers by Marc Höglinger
This network shows the impact of papers produced by Marc Höglinger. 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 Marc Höglinger. The network helps show where Marc Höglinger may publish in the future.
Co-authors
The 25 scholars most cited alongside Marc Höglinger, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 74 | |
| 2 | 2018 | 48 | |
| 3 | 2017 | 40 | |
| 4 | 2016 | 36 | |
| 5 | 2020 | 25 | |
| 6 | 2021 | 15 | |
| 7 | 2022 | 11 | |
| 8 | 2019 | 9 | |
| 9 | 2022 | 7 | |
| 10 | 2022 | 7 | |
| 11 | 2022 | 7 | |
| 12 | 2021 | 5 | |
| 13 | 2015 | 4 | |
| 14 | 2020 | 3 | |
| 15 | 2020 | 3 | |
| 16 | 2024 | 2 | |
| 17 | 2020 | 2 | |
| 18 | 2020 | 2 | |
| 19 | 2021 | 1 | |
| 20 | 2021 | 1 |
About Marc Höglinger
Marc Höglinger is a scholar working on Epidemiology, Clinical Psychology, Modeling and Simulation, General Health Professions and Economics and Econometrics, having authored 22 papers that have together received 303 indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (6 papers), COVID-19 and Mental Health (6 papers), Survey Sampling and Estimation Techniques (4 papers), Hate Speech and Cyberbullying Detection (4 papers), COVID-19 Digital Contact Tracing (3 papers), COVID-19 Pandemic Impacts (3 papers), Privacy, Security, and Data Protection (3 papers) and Hip and Femur Fractures (2 papers). The work is most often cited by research in Statistics and Probability (99 citations), Modeling and Simulation (31 citations), Information Systems (85 citations), Sociology and Political Science (128 citations) and Health (22 citations). Marc Höglinger has collaborated with scholars based in Switzerland, Germany and Canada. Frequent co-authors include Ben Jann, Andreas Diekmann, André Moser, Viktor von Wyl, Milo A. Puhan, Tala Ballouz, Dominik Menges, Marco Kaufmann, Chloé Sieber and Anja Frei. Their work appears in journals such as PLoS ONE, JMIR Public Health and Surveillance, Swiss Medical Weekly, The European Journal of Health Economics and Telemedicine Journal and e-Health.
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.