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This article presents the results of methodological experimentation that utilises machine learning to investigate automated copyright enforcement on YouTube. Using a dataset of 76.7 million YouTube videos, we explore how digital and computational methods can be leveraged to better understand content moderation and copyright enforcement at a large scale.We used the BERT language model to train a machine learning classifier to identify videos in categories that reflect ongoing controversies in copyright takedowns. We use this to explore, in a granular way, how copyright is enforced on YouTube, using both statistical methods and qualitative analysis of our categorised dataset. We provide a large-scale systematic analysis of removals rates from Content ID's automated detection system and the largely automated, text search based, Digital Millennium Copyright Act notice and takedown system. These are complex systems that are often difficult to analyse, and YouTube only makes available data at high levels of abstraction. Our analysis provides a comparison of different types of automation in content moderation, and we show how these different systems play out across different categories of content. We hope that this work provides a methodological base for continued experimentation with the use of digital and computational methods to enable large-scale analysis of the operation of automated systems.

In 2015, the Australian government passed the Telecommunications (Interception and Access) Amendment (Data Retention) Act, which requires ISPs to collect metadata about their users and store this metadata for two years. From its conception, Australia's data retention scheme has been controversial. In this article we examine how public interest concerns were addressed in Australian news media during the Act's passage. The Act was ultimately passed with bipartisan support, despite serious deficiencies. We show how the Act's complexity seemed to limit engaged critique in the mainstream media and how fears over terrorist attacks were exploited to secure the Act's passage through parliament.