Neural Opinion Dynamics Model for the Prediction of User-Level Stance Dynamics - Yulan He, Warwick

Explore the application of machine learning techniques to digital democracy platforms in this 22-minute talk from the Alan Turing Institute. Delve into the challenges and opportunities of direct democracy initiatives, focusing on how neural opinion dynamics models can predict user-level stance dynamics. Learn about stance detection, hierarchical viewpoint discovery, and the Neural Opinion Dynamics (NOD) model. Examine case studies from the US General Election and discover how these techniques can enhance citizen engagement in policy-making. Gain insights into the intersection of collective intelligence, machine learning, and digital participation platforms, and their potential to revitalize trust in democratic processes.

Intro
Stance Detection
Twitter Datasets
Hierarchical Viewpoint Discovery
Hierarchical Opinion Phase Model
US General Election
Stance Classification Accuracy
User Stance Dynamics Prediction
Neural Opinion Dynamics (NOD) model
Problem Setup
Experimental Setup
Tracking Stance Dynamics