Tatiana Celadin
Biographic Data
| ID | 9561437 |
|---|---|
| NAME | Tatiana Celadin |
| GIVEN NAMES | Tatiana |
| FAMILY NAME | Celadin |
| SIGNATURE | CELADIN T |
| AFFILIATIONS | University of Bologna |
| ORCID | 0000-0002-7743-3117 |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 3 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2022 |
| LATEST PUBLICATION YEAR | 2023 |
| H-INDEX | 0 |
“I Think This News Is Accurate”: Endorsing Accuracy Decreases the Sharing of Fake News and Increases the Sharing of Real News
Accuracy prompts, nudges that make accuracy salient, typically decrease the sharing of fake news, while having little effect on real news. Here, we introduce a new accuracy prompt that is more effective than previous prompts, because it does not only reduce fake news sharing, but it also increases real news sharing. We report four preregistered studies showing that an “endorsing accuracy” prompt (“I think this news is accurate”), placed into the …
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…
No prominent works on this page.
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…
“I Think This News Is Accurate”: Endorsing Accuracy Decreases the Sharing of Fake News and Increases the Sharing of Real News
Accuracy prompts, nudges that make accuracy salient, typically decrease the sharing of fake news, while having little effect on real news. Here, we introduce a new accuracy prompt that is more effective than previous prompts, because it does not only reduce fake news sharing, but it also increases real news sharing. We report four preregistered studies showing that an “endorsing accuracy” prompt (“I think this news is accurate”), placed into the …
Computer Science (3 works) · 2019-20 coronavirus outbreak (2 works) · Cognitive psychology (2 works) · COVID-19 and Mental Health (2 works) · COVID-19 epidemiological studies (2 works) · Medicine (2 works) · Pandemic (2 works) · Psychology (2 works) · Artificial Intelligence (1 works) · Coronavirus disease 2019 (COVID-19) (1 works)