The draft also brings a range of welcome legal protections and clauses to enable independent scrutiny of big tech platforms.
Among these, approved researchers and the eSafety Commissioner would be expressly permitted to use “sock puppet identities” to observe and test how platforms operate.
Critics have seized upon this provision to warn of government-sanctioned fake accounts, government surveillance, or to suggest ordinary Australians would need permission to remain anonymous online.
This is not what the draft bill states. Let’s unpack what the “sock puppets” provision actually entails.
What does the bill mean by a ‘sock puppet’?
Part of the concern may stem from the term itself. Online, a “sock puppet” often means a false identity deployed deceptively – to manipulate a discussion, make one person appear to be many, harass others, or disguise the source of a message.
The draft bill, however, separates the identity from how it’s used. It defines a sock puppet simply as a “false or fictitious identity” assumed while using, or doing anything in relation to, an online service.
It then sets out distinct purposes and limits for researchers and the eSafety Commissioner. Approved researchers must work at an Australian university and have ethics approval for their online safety research. They may create controlled accounts, observe and record what those accounts encounter, test platform features, and test how a service responds to particular actions.
For approved researchers, these accounts are not a licence to manipulate other users. They’re only allowed to engage with other users as much as it’s necessary to prevent the account from being closed, such as for inactivity.
Their main purpose is to observe and test the platform itself – a well-established research technique often called a “sock puppet audit” or “algorithmic audit”.
What is a ‘sock puppet’ audit?
Let’s say we want to know whether watching conspiracy videos leads a video platform to recommend more of them: the often discussed rabbit hole effect. Using a sock puppet audit, we can test whether particular behaviours lead a platform to steer users towards different content.
We create a set of otherwise identical accounts. Half watch the videos; half do not. We can then compare what the platform recommends to each group.
Researchers have used variations of this technique to study recommendation pathways on platforms including Twitter, YouTube and TikTok.
Sock puppet audits can also help us answer another important question: does the platform treat different kinds of users differently?
Researchers can create otherwise identical accounts that differ only in an assumed characteristic – such as age, gender, cultural identity, location, or interests – and compare their experiences. Do they receive different advertisements or recommendations? Are some directed towards different content or features? Do the platform’s safety systems intervene differently?



