Главная
Study mode:
on
1
Introduction
2
Disinformation Networks
3
Framework
4
Challenges
5
Detection Performance
6
Bot Detection Performance
7
Network Construction
8
Causal Inference
9
Network Influence
10
Potential Outcomes
11
Model Details
12
Data Collection
13
Influence Score
14
Covert Disinformation
15
Social Media Platforms
16
Summary
17
Applications
18
Narrative Dependent
19
Question from Chat
20
Technical Question
21
Time Scale
22
Social Media Companies
23
Accurate Weather Prediction
24
Impact of Networks
Description:
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.

Causal Inference on Networks to Characterize Disinformation Narrative Propagation

IEEE Signal Processing Society
Add to list