Reasons Why Social Networks Make Us Vulnerable to Misinformation

Explore the complex interplay between cognitive, social, and algorithmic biases that make us vulnerable to misinformation on social networks in this 58-minute seminar by Filippo Menczer from Indiana University. Delve into network analytics, modeling, and machine learning efforts aimed at studying the viral spread of false information and developing tools to counter online manipulation of opinions. Learn about viral memes, diffusional networks, competition for attention, agent-based models, algorithmic biases, social network structures, and the role of bots in spreading misinformation. Discover the challenges in distinguishing between bots and humans, the impact of hoaxing and automated messaging, and the effectiveness of super spreaders. Gain insights into potential strategies for reducing misinformation and enhancing media literacy in the age of social media.

Intro
Disclaimer
Viral meme
Misinformation
Diffusional Network
The Obama Administration
suppressing political speech
National Report
How it spread
Source
Media Literacy
Competition for Attention
AgentBased Models
Attention Information Load
Algorithmic Bias
Homogeneity Bias
Social Biases
Social Network Structure
Social Network Models
Novelty
Bots
Designers can be clever
Can we distinguish between bots and humans
Hoaxing
Automated Messaging
Results
Cross Communication
Super Spreaders
More Bots
Are They Effective
SB 277
How to Reduce Misinformation
Summary