S. Falsaperla
- Geophysics top 2%
- Artificial Intelligence top 5%
- Atmospheric Science top 10%
- Management, Monitoring, Policy and Law top 5%
- Sociology and Political Science
- Co-authors
- H. LangerS. SpampinatoGiuseppe Di GraziaBoris BehnckeGary M. ThompsonMarco NeriA. MessinaGemma Musacchio
- Topics
- Seismology and Earthquake Studies (20 papers)earthquake and tectonic studies (20 papers)Geological and Geochemical Analysis (18 papers)
In The Last Decade
S. Falsaperla
50 papers receiving 1.0k citations
Peers
Comparison fields: 5 of 81
- Geophysics 775
- Artificial Intelligence 449
- Atmospheric Science 105
- Management, Monitoring, Policy and Law 91
- Sociology and Political Science 75
Countries citing papers authored by S. Falsaperla
This map shows the geographic impact of S. Falsaperla'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 S. Falsaperla with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites S. Falsaperla more than expected).
Fields of papers citing papers by S. Falsaperla
This network shows the impact of papers produced by S. Falsaperla. 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 S. Falsaperla. The network helps show where S. Falsaperla may publish in the future.
Co-authorship network of co-authors of S. Falsaperla
This figure shows the co-authorship network connecting the top 25 collaborators of S. Falsaperla. A scholar is included among the top collaborators of S. Falsaperla 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 S. Falsaperla. S. Falsaperla 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 | 18 | |
| 3 | 2 | |
| 4 | 27 | |
| 5 | 4 | |
| 6 | 9 | |
| 7 | 6 | |
| 8 | 6 | |
| 9 | Can Building Seismic Resiliency Benefit from Emergent Technologies? Case Studies from the Projects KnowRISK and 3DTeLC | 1 |
| 10 | 14 | |
| 11 | The KnowRISK project - Know your city, Reduce seISmic risK through non-structural elements | 1 |
| 12 | Multistation alarm system for eruptive activity based on the automatic classification of volcanic tremor: specifications and performance | 1 |
| 13 | 21 | |
| 14 | The Contribution to Earth Science Outreach from the Staff of Istituto Nazionale di Geofisica e Vulcanologia (Italy) | 1 |
| 15 | 26 | |
| 16 | 3 | |
| 17 | 5 | |
| 18 | 20 | |
| 19 | 51 | |
| 20 | 26 |
About S. Falsaperla
S. Falsaperla is a scholar working on Geophysics, Artificial Intelligence and Management, Monitoring, Policy and Law, having authored 51 papers that have together received 1.1k indexed citations. Recurring topics across this work include Seismology and Earthquake Studies (20 papers), earthquake and tectonic studies (20 papers) and Geological and Geochemical Analysis (18 papers). The work is most often cited by research in Geophysics (775 citations), Artificial Intelligence (449 citations) and Management, Monitoring, Policy and Law (91 citations). S. Falsaperla has collaborated with scholars based in Italy, Portugal and Iceland. Frequent co-authors include H. Langer, S. Spampinato, Giuseppe Di Grazia, Boris Behncke, Gary M. Thompson, Marco Neri, A. Messina, Gemma Musacchio, R. Campanini and Matteo Masotti. Their work appears in journals such as Journal of Geophysical Research Atmospheres, Scientific Reports and Earth and Planetary Science Letters.
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.