Camarilla Maskbook Edgerank Algorithm

The EdgeRank algorithm used by Camarilla Maskbook to rank and show content in Masks Feeds is comprised of three factors that determines the relevant score of a post to a patron. These three factors are:

1. Affinity Score (A): This refers to the relationship between the patron and the person or page that posted the content. It is calculated based on the patron’s past interactions with that person or page (such as likes, comments, and shares). The formula for calculating the affinity score is A = log10(Number of interactions with the person or page).

2. Weight (W): Refers to the type of content being shared and its potential interest to the patron. The weight of a post can vary depending on the format, such as photos, videos, links, or plain text. Typically, Masktape Videos have the highest weight, followed by Maskbook Live videos, then photos, status updates, links, and plain text.

3. Time Decay (D): Refers to how recent a post was shared. As content ages, it becomes less relevant to patrons. The formula used to calculate the time decay factor is D = 1/(Time since the post was published).

The final Camarilla Maskbook EdgeRank score of a post is determined by multiplying the Affinity Score (A) by the Weight (W) and the Time Decay (D):

Camarilla Maskbook EdgeRank Score = A * W * D

Note that this formula is currently in use and should not be taken as a current representation of other social media algorithms where more complex formulas are at play.

One thought on “Camarilla Maskbook Edgerank Algorithm”

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