hyde231 / pornstar-lookup

Pornstar-Lookup

NSFW !!!

Aggregating and listing 271,658 individual pornstars with 479,247 aliases, based on 472,247 raw entries scraped from 23 different sources into a single JSON file.

Purpose

This is an attempt to combine female pornstar identities that have different names according to different sources. By using heuristics on names and aliases used, there should be a way to find similarities and link duplicates together.

Sources

Site	Merged	Index scraped	Entries scraped	Entries	Names / Aliases	Bio / Data	X-References	Remark
https://www.freeones.xxx/	true	true	true	50315	77919	true
https://www.indexxx.com/	true	true	true	51525	85085		true
https://thenude.com	true	true	true	39060	96193	true	true
https://www.eurobabeindex.com/	true	true	true	5118	25318		true
https://www.pornpics.com/	true	true		18950	37469
https://www.babepedia.com/	true	true	true	29952	59331	true	true
http://www.boobpedia.com/	true	true	true	10851	29333	true	true	pornstars only
https://www.adultdvdempire.com/	true	true	true	11282	19242	true		female only
https://metadataapi.net/	true	true		18981	18981			female only
https://www.mypornstarbook.net/	true	true		3687	3687
https://www.kindgirls.com/	true	true	true	1441	3182
http://www.pornteengirl.com	true	true		5574	5574
http://www.data18.com	true	true		12438	12438			female only
https://www.porn-star.com/	true	true		8627	8627
https://www.tiava.com/	true	true		13947	13947			female only
http://www.egafd.com/	true	true		13780	34063
http://www.bgafd.co.uk/	true	true		2733	6661
https://www.pornhub.com/	true	true	true	14841	36407	true		female only, pornstars only
https://www.iafd.com/	true	true	true	83326	144425	true		female only with debut from 1990 on
https://www.europornstars.com/	true	true	true	5549	11602	true
https://www.hotmovies.com/	true	true	true	19979	28315	true
http://www.adultfilmdatabase.com/	true	true	true	7800	25906	true	hardly	female only
http://peachy18.com/	true	true	true	42671	45527		true
https://thelordofporn.com/		true	true	1646	3874	true	true
https://findpornface.com/		true	true	29559	57435	true
Unmerged sum				503632	890541

The challenge is to create a combined list, that does not include 400000 entries but groups as many duplictes as possible.

Data Browser

The data is provided in pure JSON format, however, a very minimalistic web app is provided to explore the data. This is currently limited to ids and names/aliases, see the JSON file

Installation

• Prerequisites: Git & Node.js installed
• git clone this repo into a project directory of your choice
• unzip /src/data/Pornstars.combined.json.zip into same directory (necessary due to github filesize limit, it seems)
• npm install install dependencies within that projet directory
• npm start
• Open http://localhost:3000 to view it in the browser (takes some time to load).

Method of aggregation

...to be updated...

Example of the combined data

In the example below, the performer is listed with the id 'adrianna-sage' (with double n) on tpdb, but as 'adriana-sage' on indexxx and freeones. In a similar way all the names and aliases are stored with the mentioning source attached.

• 'ids' lists the unique part of urls from scraped sources. For example an id of "Adriana Sage_11565" from thenude refers to the uinque page https://www.thenude.com/Adriana%20Sage_11565.htm
• 'names' collects names and aliases used according to the different sources

{
	"uuid": "d830ed47-0e58-4edd-89a7-d42a0b496389",
	"ids": {
		"adriana-sage": [
			"freeones",
			"indexxx"
		],
		"Adriana_Sage": [
			"babepedia"
		],
		"adriana+sage": [
			"pornpics"
		],
		"adriana_sage": [
			"data18",
			"pornstar",
			"mypornstarbook"
		],
		"/27419/adriana-sage-pornstars": [
			"adultempire"
		],
		"adriana-sage/565": [
			"kindgirls"
		],
		"Adriana Sage_11565": [
			"thenude"
		]
	},
	"names": {
		"Adriana Sage": [
			"freeones",
			"babepedia",
			"pornpics",
			"data18",
			"adultempire",
			"pornstar",
			"mypornstarbook",
			"kindgirls",
			"indexxx",
			"thenude"
		],
		"Adriana": [
			"freeones",
			"pornpics",
			"indexxx",
			"thenude"
		],
		"Maryjane": [
			"ATKingdom",
			"indexxx",
			"thenude"
		],
		"Adrianna": [
			"indexxx",
			"thenude"
		],
		"Adrianna Sage": [
			"indexxx",
			"thenude"
		],
		"Adrian Sage": [
			"thenude"
		],
		"Adrian": [
			"thenude"
		],
		"Adriana M": [
			"thenude"
		],
		"Adrianna-sage": [
			"thenude"
		],
		"Alana": [
			"thenude"
		],
		"Alana Moreno": [
			"thenude"
		],
		"Lana": [
			"thenude"
		],
		"Rosa": [
			"thenude"
		]
	},
	"dataRef": {}
}

Todo

Other potential sources to scrape:

• https://www.dvderotik.com/en/pornostars
• http://www.babesandstars.com/
• http://www.awmdb.com/browse/starsbyletter/A/
• https://www.brdteengal.com/228/model/violla-a/
• https://www.eroticbeauties.net/model/zoey-kush/
• https://pornstarbyface.com/Girls
• https://www.elitebabes.com/top-rated-babes/page/3/
• http://www.definebabe.com/models/a/page8/
• http://albagals.com/category/i/
• https://www.worldsex.com/pornstars/sandraluberc/
• https://pornsites.xxx/pornstars/Piper-Perri

Future use of the data

The data allows to search for names / aliases and get references to profile pages of numerous aggregators for identification purposes.

If individual data can be added, the grouping algorithm could be much more precise and allow for true uuids.