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Are Anonymity-Seekers Just like Everybody Else? An Analysis of Contributions to Wikipedia from Tor

IEEE via YouTube

Overview

This course aims to analyze the contributions to Wikipedia from Tor users and evaluate whether anonymity-seekers behave similarly to other contributors. The learning outcomes include understanding the history of Tor editing on Wikipedia, comparing contributions from Tor users to other groups, and assessing the quality of content contributed by Tor users. The course teaches skills such as data analysis, measuring revert rates, binary classification, machine learning, and topic modeling. The teaching method involves utilizing various data sources and analytical techniques to draw conclusions. This course is intended for individuals interested in user-generated content, online anonymity, data analysis, and the impact of privacy-enhancing proxies on online platforms.

Syllabus

Introduction
Background
Main Contributions
Extracting the Top
The History of Wikipedia
Revert Rate
Position Tokens
Binary Classification
Machine Learning
Topic Modeling
Conclusion
Thank you

Taught by

IEEE Symposium on Security and Privacy

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