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Managing Your Profile

Your profile and settings are where you steer Headlinne directly. Learn how to manage your username, interests, regions, and recommendation profile.

By Headlinne Editorial Team · Updated on

Where you take direct control

Most of Headlinne's personalization happens automatically from how you read. But settings is where you take the wheel directly—setting your username, declaring interests, and managing how the system learns you.

It is the difference between letting the feed learn you passively and telling it explicitly what you want.

What you can manage

Your settings let you:

  • Update your profile and username
  • Choose interests—topics you want more or less of
  • Set regional preferences for local relevance
  • Review your reading and search history
  • Reset your recommendation profile for a clean slate

Interests: the direct lever

The interests controls are the fastest way to shape your feed on purpose. Marking topics and regions as interested raises them in your ranking; marking them disliked lowers them. This complements the passive learning from your swipes and reads.

If your feed is not quite right, adjusting interests here is quicker than waiting for behavior to shift it.

Resetting when you need to

If your feed has drifted—old interests lingering, a binge that skewed it—settings also lets you reset your recommendation profile entirely, clearing the learned profile so the feed rebuilds from scratch.

See resetting your recommendations for what a reset does and how the feed rebuilds afterward.

Key takeaways

  • âś“Settings is where you steer Headlinne directly, beyond passive learning.
  • âś“You can manage your username, interests, regions, and history.
  • âś“Marking interests interested or disliked is the fastest way to shape your feed.

Frequently asked questions

How do I tell Headlinne I want more of a topic?

Mark it as an interest in settings, follow the topic, and read and swipe toward related stories. Marking a topic disliked reduces it. These direct controls complement the automatic learning.

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