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Twitch will use machine learning to catch trolls evading the ban


Twitch is introducing a new machine learning feature to help streamers protect their channels from people trying to avoid bans. Named “Suspicious User Detection”, the tool will automatically tag individuals suspected of being “probable” or “possible” evaders.

In cases involving the former, Twitch will prevent any messages they send from being displayed in the chat. They will also identify these individuals for streamers and any mods that help them with their channel. At that point, they can decide if they want to ban that person. By default, possible recurring trolls can send chat messages, but they will also be flagged by the system. In addition, Twitch says creators have the option to prevent them from sending any messages.

Twitch

“The tool runs a machine learning model that takes into account a number of signals – including, but not limited to, user behavior and account characteristics – and compares that data with orders previously banned on the creator channel to assess the likelihood of an account avoiding a previous ban. at the channel level, ”a Twitch spokesman told Engadget when we asked him about the signals the system uses to detect potential violators.

Although Twitch plans to include suspicious user detection for everyone, the tool will not automatically ban users for streamers. This is designed because it is impossible to create a machine learning tool that is 100 percent accurate in any context. “You are an expert when it comes to your community and you should make the final decision on who can participate,” the company said. “The tool will learn from the actions you take, and the accuracy of its predictions should improve over time.”

The introduction of the tool follows a summer in which Twitch struggled to curb a phenomenon called the “hate attack”. The attacks have led to malicious individuals using thousands of bots for hate speech spam channels. In many cases, they targeted creators from marginalized communities. Hate raids have become such a common feature of the platform that some creators have left Twitch for a day at the company.

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Naveen Kumar

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