Predicting Susceptibility to Social Bots on Twitter

Explore the intricacies of social bot interactions on Twitter in this Black Hat USA 2013 conference talk. Delve into research examining user susceptibility to social bots and the factors that predict engagement. Learn how Klout scores, friend counts, and follower numbers can indicate a user's likelihood of interacting with bots. Discover the effectiveness of the Random Forest algorithm in classifying susceptible users when combined with feature ranking algorithms. Examine the correlation between extraversion and bot interaction, and its implications for eLearning-based awareness training. Gain insights into the evolving social bot landscape, including their growing intelligence and attempts to engage users for promotional purposes. Understand the potential for bot creators to exploit this knowledge to increase response rates. Explore the methodology, limitations, and future research directions in this field, equipping yourself with valuable knowledge to navigate the complex world of social media interactions and bot detection.

Introduction
Who Cares
Political Bots
The Truth Tea Project
Bosch Math
Methodology
Limitations
Personality
Machine Learning
Data Science
Models
Balance Data
Features
Experiments
Weka
Results
Discussion
Conclusions
Future research
Conclusion