LinkLonk - A link aggregator with a trust system

lonk
Sun, 27 Dec 2020 18:35:52 +0000

I built a link sharing website where you connect to users that share your interests. When you upvote a link - you connect to other users who upvoted that link and LinkLonk shows you what else these users upvoted.

The more in common you have with another user the more prominently their other recommendations appear on your list.

The intuition is that the more useful your past recommendations have been for me, the more I can trust your future recommendations.

This is how trust works in meatspace - we keep track of how positive our experiences have been with other people and use that track record to decide who we can trust in the future.

Except that mechanism does not work online. It just does not scale to the numbers of users we interact with. We can remember around 150 other people (the Dunbar number). Beyond that our builtin trust mechanism breaks down. We revert to more coarse and primitive trust mechanisms such as tribalism and mistrust in everyone.

While we cannot personally keep track of every user on a platform - that is what computers are good at.

That is the idea behind LinkLonk. You don't need to remember the names of users who you can trust (in fact there are no usernames on LinkLonk). You simply upvote content that was useful to you and LinkLonk constantly keeps track of how useful every other user has been and ranks new content accordingly.

Another important part of trust is that if you misplace your trust in someone and they let you down then you need a mechanism to stop trusting them.

This is what the downvote button is used for: when you downvote an item, LinkLonk reduces your “trust” in other users that upvoted it. As a result, you will see less content from those users.

The above describes the basic idea. There are a couple more concepts:

You start off weakly connected to all users, which means that at first you see content sorted by popularity. Rate something and refresh the page - the ranking will change.

You are not limited to a single persona/interest. If you have multiple interests then you can create a separate collection for each of your interests. When you upvote a link you can choose what collection it belongs to. For example, if you are interested in woodworking and music then you can create two collections and put woodworking links into one and music links into the other. Then other people who liked your woodworking recommendations will only see your other recommendations from the same collection and will not get your music. This is mostly a way for you to help other users find relevant content. It’s optional. You can put everything into the “default” collection if you don’t feel like organizing.

LinkLonk has another source of recommendations - RSS feeds. When you upvote a blog post LinkLonk connects to the RSS feed of that blog - as if it was another user. LinkLonk pulls updates from the feed and shows you the new entries using the same ranking algorithm: the more you upvote items from the feed the higher the other items from the feed are ranked. You can submit any RSS url and LinkLonk will connect (subscribe) you to it. My hope is that in the early days when we don't have many users you would find LinkLonk useful as a sort of an RSS reader.

Moderation. When you downvote an item then you get connected to other users who also downvoted that same item. In other words, you will trust their other downvotes. If they downvote something then that item will rank lower for you.

Give it a try at: https://linklonk.com/register with 'tildes' as the invitation code. The invitation code can be used multiple times and I will keep it active for a few days. After that please DM me to get a fresh code.

I’m posting this on Tildes in part because I like the group of people that Tildes has attracted. And I also feel the topics of trust systems, content curation and moderation are relevant to Tildes and to its users (see: https://docs.tildes.net/future-plans#trustreputation-system-for-moderation).

What do you think?

Comments URL: https://tildes.net/~tech/u7f/linklonk_a_link_aggregator_with_a_trust_system

Votes: 27

Comments: 26