Data Analysis

The Pornstar Index

Much to my dismay, I came to be acquainted to the fact that all major x-rated websites have an index for tracking the most popular pornstars on their catalog. Since I’m in the business of tracking and ranking different aspects of the human life, I was fascinated by the mechanics of measuring human lust. So I consulted Google and picked the top 3 websites to dissect their ranking formula.

Straight into the sample videos, I glimpsed at the data aspects captured by the website. First, the names (with profile links) of actors participating in the act, then the usual social media metrics (views, likes, downloads, comments), and last and most crazy is a percentage known as porn clarity – I don’t know if this is how much “you see” or video clarity but the heck, may be it matters to the perverted souls.

All this meta information is extracted and put on an actors profile to generate total views accrued, profile hits, tag words associated with them, production companies they’ve worked with, last active date, average porn clarity, age and country. The data is crunched through a probabilistic model  to compute a number to rank the actor.

It turns out the top ranked female pornstar by all 3 websites is Lisa Ann , a 43 year old Sarah Palin look alike who shot to prominence by starring in  ‘Who’s Nailing Palin?’ a series of six adult movies depicting the former Alaska Governor in office romance . Lisa is closely followed by Mia Khalifa, a 22 year old Lebanese pornstar who has only shot 16 movies (Lisa shot 3,500) but ranks 1st in Lebanon, 1st in Asia and 5th in the world. Wonder why? Because her profile has the highest hit for the keywords words “teen” and “amateur” which apparently are the most searched words in this business.

It’s quite fascinating on the level of sophistication employed to measure human lust, which highly correlates with human wants – a subject I’m interested in. By defining voting as a human want , the same methodology/index can be deployed to rank presidential candidates from debate videos and correlated search terms. That’s my next research project.

 

Just realized there’s another index in development, the Porn Scene Index that extracts and ranks scenes from porn videos. It checks for commonalities with other highly watched movies, if users paused or rewind at the scene. This could be handy for Google Image search and YouTube search 😉

 

 

 

 

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2 comments

  1. Hahaha so how much time did you spend exactly rewinding at particular scenes? and what genre were you mostly interested in? Cytherea? Trannies?

    Like

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