Daniela Paolotti
Impact in
- Modeling and Simulation top 1%
- COVID-19 epidemiological studies
- Health top 5%
- Vaccine Coverage and Hesitancy
Papers in
- Epidemiology 31
- Data-Driven Disease Surveillance 23
- Influenza Virus Research Studies 19
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- COVID-19 epidemiological studies 23
- Co-authors
- Daniela Perrotta (10 shared papers)Michele Starnini (8 shared papers)Nicola Perra (9 shared papers)Michele Tizzoni (12 shared papers)Ken Eames (5 shared papers)Alessandro Vespignani (9 shared papers)Vittoria Colizza (12 shared papers)Ciro Cattuto (11 shared papers)
- Journals
- Journal of Medical Internet Research (6 papers)JMIR Public Health and Surveillance (6 papers)PLoS ONE (4 papers)PLoS Computational Biology (4 papers)Scientific Reports (3 papers)
- Partner nations
- ItalyUnited StatesUnited Kingdom
In The Last Decade
Daniela Paolotti
75 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 134
- Modeling and Simulation 263
- Health 121
- Epidemiology 468
- Communication 88
- Health Informatics 16
Countries citing papers authored by Daniela Paolotti
This map shows the geographic impact of Daniela Paolotti'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 Daniela Paolotti with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniela Paolotti more than expected).
Fields of papers citing papers by Daniela Paolotti
This network shows the impact of papers produced by Daniela Paolotti. 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 Daniela Paolotti. The network helps show where Daniela Paolotti may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniela Paolotti, 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 77 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2013 | 122 | |
| 2 | 2020 | 97 | |
| 3 | 2020 | 87 | |
| 4 | 2010 | 60 | |
| 5 | 2017 | 52 | |
| 6 | 2015 | 49 | |
| 7 | 2017 | 46 | |
| 8 | 2003 | 37 | |
| 9 | 2017 | 37 | |
| 10 | 2014 | 34 | |
| 11 | 2017 | 32 | |
| 12 | 2021 | 32 | |
| 13 | 2014 | 32 | |
| 14 | 2017 | 28 | |
| 15 | 2011 | 26 | |
| 16 | 2023 | 25 | |
| 17 | 2019 | 25 | |
| 18 | 2019 | 25 | |
| 19 | 2020 | 24 | |
| 20 | 2024 | 23 |
About Daniela Paolotti
Daniela Paolotti is a scholar working on Epidemiology, Modeling and Simulation, Sociology and Political Science, Artificial Intelligence and Health, having authored 77 papers that have together received 1.3k indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (23 papers), Data-Driven Disease Surveillance (23 papers), Influenza Virus Research Studies (19 papers), Misinformation and Its Impacts (11 papers), Complex Network Analysis Techniques (7 papers), Hate Speech and Cyberbullying Detection (6 papers), Vaccine Coverage and Hesitancy (6 papers) and Particle Dynamics in Fluid Flows (4 papers). The work is most often cited by research in Modeling and Simulation (263 citations), Health (121 citations), Epidemiology (468 citations), Communication (88 citations) and Health Informatics (16 citations). Daniela Paolotti has collaborated with scholars based in Italy, United States and United Kingdom. Frequent co-authors include Daniela Perrotta, Michele Starnini, Nicola Perra, Michele Tizzoni, Ken Eames, Alessandro Vespignani, Vittoria Colizza, Ciro Cattuto, Kyriaki Kalimeri and Carl Koppeschaar. Their work appears in journals such as Journal of Medical Internet Research, JMIR Public Health and Surveillance, PLoS ONE, PLoS Computational Biology and Scientific Reports.
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.