JAKARTA - The phenomenon of TikTok with its post sharing feature based on an algorithm has made other media companies a commotion. Imitating is the easiest way to avoid bouncing off the increasingly fierce competition on social media.

Twitter Inc., is now starting to expand how to recommend posts from accounts that users don't follow. The announcement was made by the social media company on Tuesday, September 20.

As part of this expansion, it is also useful to build tools for users to control and provide feedback about that content.

"With millions of people signing up for Twitter every day, we want to make it easier for everyone to connect with the accounts and Topics they care about," Twitter said in a blog post.

The experiment comes as the social media company doubled down this year on what they call "unlinked content," or posts from accounts that users don't follow. Especially after the short video app TikTok rose to prominence by relying entirely on algorithm-driven suggestions instead of being followed by user accounts.

“Among the new designs Twitter has tested is the placement of “related tweets” under conversations on the tweet detail page,” said Angela Wise, senior director of product management in charge of “inventions” on the service.

The blog post also explains that, Twitter is also experimenting with an "X" tool that users can click on to remove recommended tweets they don't like from their timeline.

While their competitor Meta Platforms Inc., is also targeting to double the percentage of recommended content that fills its user feeds on Facebook and Instagram, by the end of 2023. This was also revealed from Meta last July.

Twitter made a few big changes from that, having embraced recommended tweets on its home timeline since 2014, though at least some of its redesigns also include a copy to TikTok.

In one recent experiment that presented a choice between an algorithmic and chronological version of the home timeline, Twitter renamed the algorithmic version "For You", the same as the TikTok main page.

Twitter's Wise says the company's discovery efforts are mostly aimed at new users, who don't yet know which accounts to follow and generally send companies fewer signals about their interests than prolific old tweeters.

Some users have complained about "related tweets" exposing them to irrelevant hyperpartisan content and creating confusion about which tweets are part of the conversation and which algorithms suggest.


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