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Federation Bot
Federation Bot
@Federation_Bot  ·  activity timestamp 2 months ago

Account Suggestions that prioritize what you like and who your friends follow — not just based on follower counts.

Hide suggestions you don't want. The algorithm adapts to you.

This is discovery done right.



Shipping soon to mobile & web 🚀



Source: https://github.com/joinloops/loops-server/blob/main/app/Services/AccountSuggestionService.php#L184



#Loops #AccountSuggestions #SmartDiscovery

An infographic titled "How Loops Finds Your Next Favorite Account," illustrating the algorithm process in three steps.

The Candidate Pool: On the left, a crowd of diverse user avatars enters a funnel labeled "The Filters." Profiles that are "Already Followed," "Hidden/Blocked," "Inactive/No Bio," or "Not Local" are shown falling out of the bottom of the funnel, while valid profiles pass through.

The Personal Recipe: In the center, the valid profiles enter a mixing bowl metaphor to be scored. Three measuring scoops pour ingredients into the bowl, representing the scoring weights: a large purple scoop for "Shared Interests (60%)," a medium green scoop for "Mutual Connections (30%)," and small spoons for "Creator Activity (7%)" and "Popularity (3%)."

Your Recommendations: On the right, the result flows into a smartphone screen displaying a list of profile cards. The top card is highlighted as a "Top Match" with a 98% match score, followed by other profiles with 92% and 87% match scores
An infographic titled "How Loops Finds Your Next Favorite Account," illustrating the algorithm process in three steps. The Candidate Pool: On the left, a crowd of diverse user avatars enters a funnel labeled "The Filters." Profiles that are "Already Followed," "Hidden/Blocked," "Inactive/No Bio," or "Not Local" are shown falling out of the bottom of the funnel, while valid profiles pass through. The Personal Recipe: In the center, the valid profiles enter a mixing bowl metaphor to be scored. Three measuring scoops pour ingredients into the bowl, representing the scoring weights: a large purple scoop for "Shared Interests (60%)," a medium green scoop for "Mutual Connections (30%)," and small spoons for "Creator Activity (7%)" and "Popularity (3%)." Your Recommendations: On the right, the result flows into a smartphone screen displaying a list of profile cards. The top card is highlighted as a "Top Match" with a 98% match score, followed by other profiles with 92% and 87% match scores
An infographic titled "How Loops Finds Your Next Favorite Account," illustrating the algorithm process in three steps. The Candidate Pool: On the left, a crowd of diverse user avatars enters a funnel labeled "The Filters." Profiles that are "Already Followed," "Hidden/Blocked," "Inactive/No Bio," or "Not Local" are shown falling out of the bottom of the funnel, while valid profiles pass through. The Personal Recipe: In the center, the valid profiles enter a mixing bowl metaphor to be scored. Three measuring scoops pour ingredients into the bowl, representing the scoring weights: a large purple scoop for "Shared Interests (60%)," a medium green scoop for "Mutual Connections (30%)," and small spoons for "Creator Activity (7%)" and "Popularity (3%)." Your Recommendations: On the right, the result flows into a smartphone screen displaying a list of profile cards. The top card is highlighted as a "Top Match" with a 98% match score, followed by other profiles with 92% and 87% match scores
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GitHub

loops-server/app/Services/AccountSuggestionService.php at main · joinloops/loops-server

The federated short video sharing platform. Contribute to joinloops/loops-server development by creating an account on GitHub.
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