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Bluesky hits 40 million users, introduces ‘dislikes’ beta

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Bluesky hits 40 million users, introduces ‘dislikes’ beta
Social Media
Tech News
  • November 1, 2025
Bluesky Hits 40 Million Users, Introduces ‘Dislikes’ Beta

Bluesky Surpasses 40 Million Users and Introduces Beta ‘Dislikes’ Feature to Enhance Personalization

Bluesky, a decentralized social network operating on the AT Protocol, has announced it now hosts 40 million registered accounts. The platform also introduced a beta “dislikes” feature designed to refine user customization by collecting feedback on content preferences.

The dislike button lets users flag posts they wish to see less of, helping algorithms tailor recommendations in feeds like Discover. This negative signal supplements positive engagement metrics—such as likes—to better individualize content rankings while maintaining free expression.

Since its debut, Bluesky has differentiated itself from centralized rivals by allowing users to control their data and moderation settings. Its open algorithm marketplace enables personalized feeds reflecting distinct community values and interests.

This update addresses concerns about irrelevant or harmful content without heavy-handed restrictions. Additional upgrades include advanced toxicity filters and tools to elevate substantive discussions.

Reaching 40 million users signifies rapid adoption for a decentralized platform, highlighting demand for alternatives prioritizing user autonomy over corporate control amid growing privacy debates.

Despite growth, Bluesky faces challenges like inconsistent active-user rates and moderation hurdles. The team continues refining its systems using community insights and transparent data practices.

Bluesky’s leadership stated their vision is to foster “authentic, enjoyable, and courteous interactions” through user-controlled tools. The dislikes beta reflects this iterative, community-driven strategy.

Future success hinges on improving user retention, personalization accuracy, and curbing toxicity. Bluesky aims to demonstrate that decentralized, user-focused models can thrive against established networks.

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