fedialgo

Fedialgo is an typescript module, that can be used to produce an algorithmic fediverse experience. This will replace the project "fedifeed" and make it possible to implement the idea into all kinds of other projects. It uses React Native Async Storage, so it should also work in React Native Projects, but havent tested it yet.

Install directly from github:

npm install github:pkreissel/fedialgo

Local Install

Clone the repo and cd into it.

Run:

npm install
npm link

Then in your local project:

npm link fedialgo

Use // @ts-ignore if you run into Typescript warnings (because your project might also use masto)

npm run build

in fedialgo directory after changes and they will automatically be detected

Usage

Basic Feed:

import TheAlgorithm from "fedialgo"
import { login, mastodon } from "masto";

const api: mastodon.Client = await login({
                    url: user.server,
                    accessToken: user.access_token,
                });
const currUser = await api.v1.accounts.verifyCredentials()
const algo = new TheAlgorithm(api, currUser)
const feed = await algo.getFeed()

Adjust Weights:

The algorithm uses features and their weights to determine the order of the posts.

You could e.g. show the weights to the user, who can then decide to change them.

let weights = await algo.getWeights()
weights["fav"] = 0.5 // change the weight of the feature "fav" to 0.5
let newWeights = weights
const newFeed = await algoObj.setWeights(newWeights)

Learn Weights

You can also let the algorithm learn the weights from the user's behaviour. This is done by passing the scores of the posts to the algorithm. The algorithm will then adjust the weights accordingly. This is quite simple, but still has impact on the feed. For example you could choose to adjust the weight after each click on a post, after a reblog, or after a link click.

const scores = status.scores
const newWeights = await algoObj.weightAdjust(scores)

This is untested early alpha so might be due to massive unannounced changes.