Twitter is now pushing suggested tweets to everyone

Twitter is now pushing more tweets from accounts where users haven’t followed their timeline. The company revealed that it is now showing recommendations to all of its users, even those who have successfully avoided them in the past.

“We want to make sure everyone on Twitter sees the best content on the platform, so we’re expanding our recommendations to all users, including those who may not have seen them before, ” the company wrote in a tweet.

It’s not clear if this means that suggestions will start appearing in the “latest” timeline, which arranges tweets chronologically and previously did not include recommendations, or that Twitter simply does for more prominent recommendations in other parts of the app. In its tweet, the company pointed out a from September, which states that “suggestions may appear in your Home timeline, certain places in the Explore tab, and elsewhere on Twitter.”

Usually, it seems that some users have follow their timeline, with the emergence of new topic suggestions and numerous tweets from seemingly random accounts.

While the change can be frustrating, this isn’t the first time the company has experimented with adding more recommended content. Twitter has pushed recommendations into different sections of its service , although it has sometimes adjusted how often these suggestions appear. In the past, Twitter has also been careful to note that it bans certain types of content from recommendations to avoid amplifying potentially harmful or low-quality content, although it’s not entirely clear whether that’s the case. happens or not. The company no longer has a media team.

Interestingly, Twitter’s current CEO, Elon Musk, has not always spoken favorably about the platform’s recommendation algorithms. Back in May, that using the app’s “latest” timeline is important to “fix” Twitter’s feed. “You’re being manipulated by the algorithm in ways you don’t realize,” he said at the time. Musk, who also talked about his wish Twitter’s algorithms haven’t considered scaling new recommendations or how the feature works.

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