After a year of testing the feature with select web users, Twitter is now rolling out its downvote button to more users across the globe.
Twitter is rolling out its downvote feature test globally. The company began experimenting with the option about a year ago and with only a select group of web users. Now Twitter is making downvotes available to more users on Android and iOS.
According to Twitter, downvotes are negative votes that won’t function as public dislikes or change the order of relevance for replies to downvoted content. Instead, downvotes are reactions to replies sent privately to an author, intended as a tool for creators to gather feedback from the audience and use it to tailor future content.
We learned a lot about the types of replies you don't find relevant and we're expanding this test –– more of you on web and soon iOS and Android will have the option to use reply downvoting.
— Twitter Support (@TwitterSupport) February 3, 2022
Twitter says that downvotes will provide guidance and help “to understand the types of replies you find relevant in a convo, so we can work on ways to show more of them.”
Interestingly, during the testing phase, Twitter found that most downvotes expressed were linked to replies that users thought were offensive or irrelevant. As such, the downvote tool became the closest and easiest way for users to report undesirable content.
Another insight learned during the test is that users report that downvotes offer a more effective way of improving the quality of conversations on the platform and shaping the content they would like to see more of.
A couple of months ago, YouTube announced changes to its own dislike button. The thumbs-down icon was built on the video-sharing platform to gather user feedback and privately send it to the creator of the disliked video.
The change hid public dislike counts and transformed the option into a tool for feedback creators can rely upon to decide which content their audience likes best – as well as a way to inform YouTube’s algorithm about the content users would like to be recommended.
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