Ladsgroup has actively edited Wikipedia since 2006. On the Persian Wikipedia, he's a bureaucrat, oversighter and check user. He currently works as a Staff Database Architect for the WMF. As a volunteer he helps build tools for CheckUsers. This article was written in his role as a volunteer and any opinions expressed do not necessarily reflect the opinions of The Signpost, the WMF, or of other Wikipedians.

When you edit Wikipedia, it will be public. We all know that. But do you know what it actually entails?

Some trusted users called Checkusers are able to see your IP address and user agent. Meaning they will know where you live, maybe where you are studying or where you work. They don't disclose such information and it's subject to a really strong policy. However, that's not the only way you can be identified.

The way you use language is unique to you; it's like a fingerprint. There are bodies of research on that. With simple natural language processing tools, you can extract discussions from Wikipedia and link accounts that have similar linguistic fingerprints.

socks

not socks

Here's an example of two socks in Persian Wikipedia and two users that are not, analysed using a simple NLP system.

What does this mean? It means people will be able to find, guess or confirm their suspicions on other accounts you have. They will be able to link between multiple accounts without needing access to private data that could reveal where you live or work.

Wikimedia projects are public: the license means that all information hosted on them can be reused for any purposes whatsoever, and the privacy policy allows for analysis of edits or other information publicly shared for any reason.

That means anyone with resources or knowledge can analyze data trends in your edit history, such as when you edit, what words you use, what articles you have edited. As technology has advanced, tools for analyzing trends in user data have as well, and include things as basic as edit counters, and as complex as anti-abuse machine learning systems, such as ORES and some anti-vandal bots. Academics have begun utilizing public data to develop models for combatting abuse on Wikipedia using machine learning and artificial intelligence systems, and volunteer developers have created systems that utilize natural language processing in order to help identify malicious actors.

As with anything, these technologies can be abused. That's one of the risks of an open project: an oppressive government or a big company can invest in it and download Wikimedia dumps. They can even go further and cross-check it with social media posts. While not likely in most cases, in areas of the world where free speech is limited, one should be conscious of what information you share on Wikipedia and other Wikimedia projects.

Beside external entities, volunteers have been building such tools to help Checkusers do their job better, with the potential to limit access to private data. The tool we showed graphs from here is being used in several wikis already but is only made available to Checkusers of that wiki by the developer. The tool doesn't give just a number, it builds plots and graphs to make decision-making easier.

Legally, there's nothing we can do to stop external entities from using this data – it's engraved in our license and privacy policy^[1] that it's free to use for whatever purpose people see fit.

Because of this, restrictions on the use of natural language processing or other automated or AI abuse detection systems that do not directly edit Wikimedia projects are not possible. Communities could amend their local policies to prohibit blocks based on such technologies or to prohibit consideration of such analysis when deciding whether or not there is cause to use the CheckUser tool. Local projects cannot, however, prevent use of natural language processing or other tools completely because of the nature of the license and the current privacy policy.