Delivering a useable method for mapping groups in attitude networks by developing a robust prototype, development community, and exploitation model to maximize the social value of the breakthrough

Introduction

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, and allows the application of network methods to analyze their relations.

Ideological Polarization

Additionally, it 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 modeling attitudes and human behavior.

Importance of Understanding Social Processes

Understanding these processes is essential for tackling urgent social issues which require cross-partisan synchronization of core attitudes/opinions, such as:

• Climate change
• Vaccine hesitancy
• Cohesive democracy

Accessibility of the Method

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 usable form.

Project Goals

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 commercialization opportunities.
6. Determine the optimal IP strategy for maximizing the social value of the innovation.

Conclusion

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.