here is what i have tried so far, and below the challenges i’m facing.
Discussion
i would appreciate your guidance or the possibility to work together on this.
i built a system inspired by Twitter's own "Tweepcred" algorithm, which calculates user reputation based on social interactions.
social credit?
i implemented in Python and Scala using network analysis libraries.
the official Twitter open source code for Tweepcred is available and can serve as a detailed reference:
i cloned the repository on GitHub (see below)
to work together with you nostr:nprofile1qqsrhuxx8l9ex335q7he0f09aej04zpazpl0ne2cgukyawd24mayt8gprdmhxue69uhhyetvv9ujuam9wd6x2unwvf6xxtnrdakj7qg6waehxw309ac8junpd45kgtnxd9shg6npvchxxmmd9u6gptxa , we need
here is a conceptual outline in Python-style for the steps:
if you want, i can provide detailed help for any specific step or coding language.
the open-source code for programming authority and reputation on X is part of X's broader open-source recommendation algorithm repository on GitHub: "the-algorithm."
BUT IS NOT WORKING
within it, the "tweepcred" component specifically implements a PageRank-like algorithm to calculate user reputation based on interactions such as mentions and retweets from influential accounts.
this algorithm underpins how X internally measures user authority for ranking and content visibility.
“internally”… means: NOT OPEN
but, is not working. we need to make it better, perfect, and clear to get every user with a score in their profile. ( score for reputation and authority: visible - open - transparent ) a number / a color.
and we can also measure the hours they spend creating value on the platform, so then we can pay them. ( in bitcoin, of course )
GitHub repo link with tweepcred source:
for the new code:
1. data gathering from Twitter API is necessary to build the user interaction graph.
2. the algorithm needs to be translated or adapted into Python. this is my preference
3. integration involves graph construction, PageRank calculation, user mass adjustment, and score scaling.
i cloned and studied the “tweepcred” subfolder within the repo to understand implementation details.
but i know we can make it better
i know you nostr:nprofile1qqsrhuxx8l9ex335q7he0f09aej04zpazpl0ne2cgukyawd24mayt8gprdmhxue69uhhyetvv9ujuam9wd6x2unwvf6xxtnrdakj7qg6waehxw309ac8junpd45kgtnxd9shg6npvchxxmmd9u6gptxa and i can make it perfect.
and i trust we can get this done this week. ( running on nostr )
next week the project will be profitable. we’re making money
