I have several things planned, such as a content quality metric. This discourages low-quality, repetitive posts, and other low-quality influencer-like content.
Also interaction diversity, which indicates how much that person interacts with different viewpoints.
The number of different metrics we could come up with is practically limitless. As users, we want to select those algos. But of course, we can’t all be coding 18 hours a day.
I envision GrapeRank as a general purpose method to wrap our arms around the space of metrics in a way that gives users the ability to express their individual preferences without having any sort of computer expertise. The core idea is interpretation: someone (a developer) needs to write a script to collect data and synthesize it into a format that is ready for digestion by the GrapeRank algo. Interaction diversity, for example, could be “fed” into GrapeRank and synthesized with other inputs. As users, all we do is select which pieces of data, how much to weigh them, for the calculation of any given score.
So I’d love to see your metrics in action. And then my challenge will be to demonstrate that GrapeRank can implement your metrics in a manner that reflects your intentions when you designed them.
How does GrapeRank work?
Here’s a description of how it works as currently implemented.
https://grapevine-brainstorm.vercel.app/#/about/graperank
I say “as currently implemented” bc currently I’m calculating one GrapeRank score using follows and mutes and that’s it. But the idea is that we can calculate multiple GrapeRank scores, each its own context, each using distinct data inputs which are “interpreted” using unique scripts. I probably should expand upon that point in the about section.
