本文探讨了社交网络中作者和读者兴趣匹配的问题。作者认为，当前的社交网络平台更倾向于鼓励用户专注于单一领域，以便算法更好地匹配用户和内容。然而，作者本人更希望能够在社交网络上分享各种感兴趣的话题，并希望平台能够更好地匹配特定帖子与感兴趣的用户。文章指出，随着人工智能技术的进步，这种基于内容和用户偏好的帖子分类问题变得更容易解决，或许未来会有社交网络平台尝试解决这一问题，例如通过自定义订阅功能来实现。

🤔 **当前社交网络平台倾向于鼓励用户专注于单一领域，以便算法更好地匹配用户和内容。** 这使得专注于特定领域的作者更容易获得关注，但对于希望分享多样化内容的作者来说则不太友好。

🤔 **作者希望社交网络能够更好地匹配特定帖子与感兴趣的用户，而不是强迫用户选择关注某个特定领域。** 作者认为，每个人的兴趣都是多方面的，社交网络应该能够根据内容和用户偏好进行匹配。

🤔 **人工智能技术的进步使得基于内容和用户偏好的帖子分类问题变得更容易解决。** 这为社交网络平台提供了一种新的可能性，即根据帖子内容和用户喜好进行精准匹配。

🤔 **Bluesky的自定义订阅功能可能为解决此问题提供了一种途径。** 这类功能能够让用户根据自身兴趣选择订阅特定类型的内容，从而提高信息匹配效率。

🤔 **帖子分类不能完全依赖于用户手动添加标签，因为用户往往比较懒惰。** 更有效的方案可能是基于帖子内容和用户互动情况进行自动分类。

Published on November 27, 2024 3:40 AM GMT

It's rare that an author's interests will fully overlap with any givenreader's. You can choose to post anywhere on a spectrum between:

Narrow: pick a topic and make it your beat. People who careabout that can follow you and pretty reliably see what they're lookingfor.

Broad: write about whatever you like. Some readers will bewilling to scroll past posts on uninteresting topics, others willdecide the combination is too noisy to be worth it to them.

Current social network technology strongly favors the former: if youwrite about just one area it's much easier for algorithms to figureout who to show your posts to. And so you see a lot of advice to buildyour personal brand about an area: write about cooking, or housingpolicy, or military history.

This is very much not for me. I want to write about whatever I wantto write about, which is a lot of different things, and I've generallyjust accepted that this is a bad fit for Facebook and the other placespeople read my writing. But two exceptions:

Julia and I have a groupfor kid stuff, because it seems to be especially polarizing.With RSS, I (and others) have single-topicfeeds.

If this were just a me problem then it wouldn't be too bad, but thisseems pretty big to me. In trying outBluesky I'm running into a bunch of accounts that post about arange of things I find variously interesting. I can decide whetherthey're worth it overall, but this is not the right choice for thetechnology to be forcing me to make.

Instead, I've longwanted a social network built around the idea that each person'sidentity and interests have many facets, and tries to match specificposts with the people that would be interested in them.

I wonder if, at a time when advances in AI are making this kind ofclassification problem easier and there's more social networkingcompetition than there has been for a while, someone might want totake this on? Perhaps Bluesky's customfeeds would be a good way to play with this?

(I don't think this can depend on people tagging their own posts,because people are generally lazy. But something based on classifyingthe post based on its content and who has liked it so far seems prettypromising.)

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