Project description
Robust prototype software to map opinion-based groups
There is a way to construct bipartite graphs directly from opinion surveys. The ERC-funded Attitude-Maps-4-All project will do so by applying a mathematical method that will yield a network representation of opinion-based groups. The method uncovers group structure, locates individuals in the space, allows the application of network methods to analyse their relations, and detects ideological polarisation, providing new insight on social attitudes and opinions, in a wide range of disciplines related to modelling attitudes and human behaviour. Understanding these processes is essential for addressing urgent social challenges requiring cross-partisan synchronisation of core attitudes and opinions. The project will prototype a robust software architecture and training resources, test and assess them, and explore cooperation for commercialisation.
Objective
Our ERC project developed a mathematical method to construct bipartite graphs directly from surveys of attitudes and opinions, providing a network representation of opinion-based groups. This approach reveals group structure, locates individuals in the space, allows the application of network methods to analyze their relations, and can detect ideological polarization, even without extremism. Like the invention of a new instrument for observing the physical world (e.g. a telescope), the method gives a new view on social attitudes and opinions, with huge value for detecting partisan dynamics in a wide range of disciplines interested in modelling attitudes and human behaviour. Understanding these processes is essential for tackling urgent social issues which require cross-partisan synchronization of core attitudes/opinions (e.g. climate change; vaccine hesitancy; cohesive democracy). Applying these methods currently requires high-level mathematics and coding skills. To realize the social value of the method we must get it into the hands of end-users in useable form. We will (1) prototype a robust software architecture; (2) prototype training resources; (3) implement end-user testing and evaluation of the prototype software and training; (4) build a community of early adopters and developers to test, validate and evaluate the method across a range of multidisciplinary applications; (5) explore synergistic commercialisation opportunities; and (6) determine the optimal IP strategy for maximizing the social value of the innovation. Our intention is to maximize the value of the advance already achieved in our ERC project by completing the groundwork to make the innovation maximally accessible to the interdisciplinary scientific community and to identify synergistic commercialization opportunities.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
- natural sciencescomputer and information sciencessoftware
- social sciencespolitical sciencesgovernment systemsdemocracy
- medical and health sciencesbasic medicinepharmacology and pharmacypharmaceutical drugsvaccines
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Programme(s)
- HORIZON.1.1 - European Research Council (ERC) Main Programme
Funding Scheme
HORIZON-ERC-POC - HORIZON ERC Proof of Concept GrantsHost institution
- Limerick
Ireland