Link analysis between john boards, dating websites, and prostitution websites to find serial/high frequency buyers.  How it would work:

Comparison of writing style across websites.  There are a number of ways to tell if an author is the same across many mediums.  Some parts of a writers signature will vary with context, but sort phrases and word choices will be consistent across mediums, for a small period of time.  I believe the way this project would look is simple.

I'd scrape the site types mentioned above, apply the necessary nlp, to establish matching conditions, and then try to build a single person for each handle.  The expectation is that handles would change over time or that multiple handles may refer to a single person.

Deliverables:

Pictures associated with high volume consumers of commercial sex - many dating websites require you to upload pictures.  And sometimes people just do this because.

A more accurate representation of the number of active users of john boards.

A set of ontologies of terms used by members of various john boards and how that ontology evolves over time and regionally.

A greater understanding of the demand side by age, gender,ethnicity, and socio-economic class - often times people will post salary range, profession and other personal information on dating websites.

A psychological understanding of high volume buyers of sex, statistically - often times people on dating websites will answer a series of questions indicating their psychological make up, used for matching algorithms.  If we can link a profile to an investigation, a law enforcement agency could use subpoena compliance to obtain the list of questions and their answers. Such information could even be anonymized passed back to dating websites and be used to statistically flag for buyers of commercial sex by dating websites.  This level of cooperation between companies and dating websites is unlikely, but possible.

##To Dos

##Scrapers:
* Build a scraper for dating websites
* Build scrapers for all of the prostitution websites
* Do integrity testing of john board scraper/ integrate selenium scraper for deep web


##Identification of prostitution websites to scrape

* adultsearch
* alibaba
* anunico
* backpage
* cityvibe
* cityxguide
* cityxguideforum
* classivox
* craigslist
* ec21
* eroticmugshots
* eroticreview
* escortadsxxx
* escortphonelist
* escortsinca
* escortsincollege
* escortsintheus
* gmdu
* gulfjobsbank
* happymassage
* justlanded
* liveescortreviews
* manpowervacancy
* massagetroll
* missingkids
* myproviderguide
* myproviderguideforum
* naughtyreviews
* redbook
* redbook_forum
* rubads
* sipsap
* tradekey
* usasexguide
* utopiaguide

##Identification of John Boards to scrape
* usasexguide.com
* erotic review
* Eros
* city vibe

##Identification of dating websites to scrape - to do - indentify all of these
*  

##Database:
* Choose a database for storing all of this information, pulling out keywords, hard attributes, and full text
* implement the database

Visualizations:


