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Twitter is experimenting with an ‘un-mentioning’ feature

FILE - Twitter is experimenting with a feature that will allow users to remove themselves from conversations. Twitter icon on a mobile phone. File picture: Matt Rourke/AP

FILE - Twitter is experimenting with a feature that will allow users to remove themselves from conversations. Twitter icon on a mobile phone. File picture: Matt Rourke/AP

Published Apr 11, 2022

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Twitter is experimenting with an “un-mentioning” feature.

Officials at the microblogging website – which allows users to tag each other in posts by using the @ button – teased that they were slowly rolling out a feature that would allow users to remove themselves from a post they have been mentioned in.

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The Twitter Safety account said in a tweet: “How do you say ‘Don’t @ me,” without saying “Don’t @ me”?

“We’re experimenting with Unmentioning – a way to help you protect your peace and remove yourself from conversations – available on Web for some of you now.”

The tweet was accompanied with a GIF that showed how the feature – which is only available on the web version of Twitter for now – can be accessed. No announcement has been made on an official launch date across all platforms

The “leave this conversation” option will appear on the menu that pops out of the corner of a tweet on the web version of Twitter and upon quitting the conversation, the hyperlink to the user's profile via their name is immediately removed and prevents the user from being mentioned further as they stop receiving notifications.

It comes just months after the platform decided to launch Safety Mode and Autoblocks, a safeguarding feature which can be found in the settings of both mobile and web versions of Twitter.

At the time, Twitter spokesperson Jarrod Doherty said: “Safety Mode is a feature that temporarily blocks accounts for seven days for using potentially harmful language — such as insults or hateful remarks — or sending repetitive and uninvited replies or mentions.

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“When the feature is turned on in your Settings, our systems will assess the likelihood of a negative engagement by considering both the Tweet’s content and the relationship between the Tweet author and replier.”

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