The Nomic Game Schema

So I haven’t updated on the Nomic Game since the first post.

For the reader who was perplexed by the “philosophical design” of the Nomic Game, here’s where I took this crazy ramble:

Reflecting on the “philosophical design,” I produced this set of notes:

some notes i had jotted down

Don't mind the handwriting. I can read it! ;-)

From these notes, I created these tables:

| Tables_in_nomics |
| community_admins |
| community_list |
| community_members |
| error_logs |
| following |
| ideas |
| people |
| votes |

I have another table to create called “plans” which are just going to be collections of ideas. Long story short, I reasoned that a “plan” is really just the collection of a number of small ideas. I felt ‘plans’ were an important notion to capture because if the Nomic Game can generate real action (as I hypothesize is possible), then there needs to be some way to collect “ideas” into a “plan”.

What I thought was particularly interesting about my contemplation of ideas was the exploration of “sentiment.” Related to another project I’m working on, I’ve been looking through different models to understand “decay” rates. I’ve been studying up a bit on Normal Distribution, and some other fun things.

When I applied some of this decay and Normal Distribution thinking to the notion of a “sentiment,” I arrived with this basic behavior:

A general model of sentiment.

Two models for measuring sentiment.

Without divulging the exact formula(s) that I’ll be tweaking to measure sentiment, the general idea is that as an idea moves from neutrality to agreement (or disagreement), it’s also building up an “area” proportional to the number of people participating in the idea. This is important (imho) because not all ideas will garner the same attention and so we wouldn’t want to present relatively unimportant ideas to people.

Using those two models, I think I can measure “consensus” (general agree/disagree) and also “impact of consensus” (how many people actually give a sh*t).

Anyone want to help me with this part of the project? I’m not an expert at statistical modeling and it’d be great to get some pointers. :)

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