NETWORKED SOCIAL INFLUENCE AND ACCEPTANCE IN A NEW AGE OF CRISES
Abstract
In an age of emerging disruptive crises (COVID) and technologies, understanding influence in traditional and online societies is critical to defence and technologies. We know that influencers play a vital role in influencing the opinion of others and creating social acceptance. This is a vital mechanism in the dissemination of new ideas. However, what we do not understand is the effective combined mechanisms that stem from how the influencer behaves and where he/she stands in a multi-scale social network. The research aim is to understand the joint impact of individual behaviour and the wider influence from social network structure. Traditional social influence can be gauged by complex network analysis, where eigenvectors point towards influential locations on the social network. Whilst this has led to useful metrics such as PageRank, it neglects the complex nonlinear dynamic interactions between people and the multiscale topological factors that contribute towards a more sophisticated picture. Here, we set out the ambition to create a modeling framework, grounded in real and diverse social data, on how to combine complex social network analysis with nonlinear human behaviour dynamics. This has the advantage of being able to uncover hidden influencers. This has widespread applications in counterterrorism, social media analysis, and understanding how we can effectively spread policies and create acceptance to technologies in an age of emerging crises (e.g. COVID).
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Aug 12, 2021
- Source ID
- FA86552017031
Entities
People
- Weisi Guo
Organizations
- Air Force Office of Scientific Research
- Cranfield University
- United States Air Force