Causal Inference on Networks to Characterize Disinformation Narrative Propagation

Explore causal inference techniques for analyzing disinformation propagation on networks in this IEEE Signal Processing Society webinar. Delve into the challenges of detecting bots and constructing accurate network representations. Learn about influence scoring methods, potential outcome models, and data collection strategies for studying covert disinformation campaigns. Examine the impact of social media platforms and network structures on narrative spread. Gain insights into applications for countering misinformation, including time-scale considerations and comparisons to weather prediction. Engage with expert discussions on technical aspects and the role of social media companies in addressing disinformation.

Introduction
Disinformation Networks
Framework
Challenges
Detection Performance
Bot Detection Performance
Network Construction
Causal Inference
Network Influence
Potential Outcomes
Model Details
Data Collection
Influence Score
Covert Disinformation
Social Media Platforms
Summary
Applications
Narrative Dependent
Question from Chat
Technical Question
Time Scale
Social Media Companies
Accurate Weather Prediction
Impact of Networks