A new method for dynamic opinion modelling of surveys applied to vaccine hesitancy data

Información del proyecto

DYNAMOD-VACCINE-DATA

Identificador del acuerdo de subvención: 891347

DOI

10.3030/891347

Proyecto cerrado

Fecha de la firma de la CE 5 Marzo 2020

Fecha de inicio 1 Junio 2020

Fecha de finalización 31 Mayo 2023

Financiado con arreglo a

• EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions

Coste total

€ 294 886,08

Aportación de la UE

€ 294 886,08

Coordinado por

UNIVERSITY OF LIMERICK
Ireland

Periodic Reporting for period 1 - DYNAMOD-VACCINE-DATA (A new method for dynamic opinion modelling of surveys applied to vaccine hesitancy data)

Período documentado: 2020-06-01 hasta 2023-05-31

Resumen del contexto y de los objetivos generales del proyecto

The project aimed to explore the pressing global social issue of the disruption of trust in scientific progress and technological solutions, such as climate change denial and especially vaccine skepticisms. This phenomenon, in 2019 has been recognized by the World Health Organization as one of the ten most serious threats to global health.

The research project aimed at developing novel methods to explore patterns and temporal trends in real opinion systems, specifically related to vaccine opinions. While many predictive models already existed in the field of opinion dynamics, most of them were not yet applied to empirical data. The project aimed to bridge this gap by connecting state-of-the-art opinion dynamics models to survey data.

The project reached its initial goal and much more. Indeed, it provided:
- Exploration of the connection between measurements of opinions and opinion dynamics data
- Validation of the micro-dynamics of opinion dynamics models
- Exploration of opinions as a belief network
- The connection of opinion dynamics models to vaccination data

Trabajo realizado desde el comienzo del proyecto hasta el final del período abarcado por el informe y los principales resultados hasta la fecha

**Research related**
Identification and cleaning of relevant datasets
Exploration of the connection between opinion dynamics models and measurement scales
Exploration of opinions as belief systems
Development of a platform for comparing multiple opinion dynamics models
Application of models to vaccination-related data
Identification of the risk factor for multiple countries


**Career development**
Training through research in computational social science, psychometrics and social psychology
Online courses on communication, research skills and dedicated softwares
Networking within the communities of Agent-Based modeling and Social Psychology


**Communication and outreach**
Publication of 6 research articles
Curations of two websites related to the project (www.dinocarp.com and www.resinmethod.net)
Continuous updates on the project on social media, especially on Twitter (@justanormaldino)
Curation of a YouTube channel covering topics related to the project and producing 6 videos related to the project
Curation of 2 press releases resulting in the appearance in 18 news outlets, including the New York Times
Delivery of 18 talks on the project
Production of 8 repositories for the project-related material

Avances que van más allá del estado de la técnica e impacto potencial esperado (incluida la repercusión socioeconómica y las implicaciones sociales más amplias del proyecto hasta la fecha)

The project advanced significantly the state of the art in the following ways
- provided a new understanding of the relationship between psychological measurements and agent-based models [impact: agent-based model community]
- explored the possibility of producing networks of attitudes [impact: social psychology community]
- explored the connection between opinion dynamics models and data and experiments [impact: opinion dynamics community]
- discovered how social influence can impact trust in vaccination [impact: health behavior, policymakers, general public]

The effect of social influence. People who are in-between are fundamental to reach the neutrals