A mechanism for evaluating support from diverse entities
QF voting behavior is a high-dimensional vector
Cluster it and use the variation as a coefficient of voting power.
Voting behavior is a high-dimensional vector
PCA it, cluster it, and multiply the support in each cluster by the consensus index.
The evaluation on the note is a high-dimensional vector
Decompose it into attribute information and bias terms in the note/voter 1 dimension
This one dimension roughly corresponds to the political left and right
High bias terms in the notes mean that they are "supported by both the political left and right"
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This page is auto-translated from /nishio/多様な主体から支持されることを評価する仕組み using DeepL. If you looks something interesting but the auto-translated English is not good enough to understand it, feel free to let me know at @nishio_en. I'm very happy to spread my thought to non-Japanese readers.