Raffaele Tucciarelli
Biographic Data
| ID | 9487284 |
|---|---|
| NAME | Raffaele Tucciarelli |
| GIVEN NAMES | Raffaele |
| FAMILY NAME | Tucciarelli |
| SIGNATURE | TUCCIARELLI R |
| AFFILIATIONS | Birkbeck, University of London |
| ORCID | 0000-0002-0342-308X |
| VERIFIED | Yes |
| TOTAL WORKS | 4 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 4 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2020 |
| LATEST PUBLICATION YEAR | 2022 |
| H-INDEX | 0 |
National identity predicts public health support during a global pandemic
Changing collective behaviour and supporting non-pharmaceutical interventions is an important component in mitigating virus transmission during a pandemic. In a large international collaboration (Study 1, N = 49,968 across 67 countries), we investigated self-reported factors associated with public health behaviours (e.g., spatial distancing and stricter hygiene) and endorsed public policy interventions (e.g., closing bars and restaurants) during …
Predicting attitudinal and behavioral responses to Covid-19 pandemic using machine learning
At the beginning of 2020, COVID-19 became a global problem. Despite all the efforts to emphasize the relevance of preventive measures, not everyone adhered to them. Thus, learning more about the characteristics determining attitudinal and behavioral responses to the pandemic is crucial to improving future interventions. In this study, we applied machine learning on the multi-national data collected by the International Collaboration on the Social…
Mapping visual spatial prototypes: Multiple reference frames shape visual memory
Tactile distance adaptation aftereffects do not transfer to perceptual hand maps
No prominent works on this page.
Mapping visual spatial prototypes: Multiple reference frames shape visual memory
Tactile distance adaptation aftereffects do not transfer to perceptual hand maps
National identity predicts public health support during a global pandemic
Changing collective behaviour and supporting non-pharmaceutical interventions is an important component in mitigating virus transmission during a pandemic. In a large international collaboration (Study 1, N = 49,968 across 67 countries), we investigated self-reported factors associated with public health behaviours (e.g., spatial distancing and stricter hygiene) and endorsed public policy interventions (e.g., closing bars and restaurants) during …
Predicting attitudinal and behavioral responses to Covid-19 pandemic using machine learning
At the beginning of 2020, COVID-19 became a global problem. Despite all the efforts to emphasize the relevance of preventive measures, not everyone adhered to them. Thus, learning more about the characteristics determining attitudinal and behavioral responses to the pandemic is crucial to improving future interventions. In this study, we applied machine learning on the multi-national data collected by the International Collaboration on the Social…
Computer Science (4 works) · Artificial Intelligence (3 works) · Psychology (3 works) · 2019-20 coronavirus outbreak (2 works) · Artificial Intelligence (2 works) · Cognitive psychology (2 works) · Communication (2 works) · Computer vision (2 works) · COVID-19 and Mental Health (2 works) · COVID-19 epidemiological studies (2 works)