REALITY CHECKS NEVER BOUNCE
Predicting Virulence of posted memes
« on: 2010-04-12 08:52:13 »
1. The words are the most powerful Memes.
A tagging system where resources (information, links, or simply text) are marked with strings of tags
1. Every tag has an initial virulence value of Unknown, or a floating point number in the range of 0.0.
2. A string of tags (words) represents a single Bookmark (a meme-complex) with one or more resources (text or URL's)
3. The game is multiplayer and everyone can share bookmarks of information in the forms URLS, blogs entries or simple text.
4. Each time someone copies a Bookmark (and possibly rates it) the virulence of the attached informational resources increases with some value ( or function depending on rating and fixed increase)
5. Splicing of Bookmarks and Tags is to be allowed, where by splice i mean when two or more Bookmarks and their tags are being combined by people and their virulence gets updated and moderated by the users.
6. Predicting Virulence.
You can predict virulence on the fly during entering the tags. when words match a small number is displayed for the virulence of the word or the whole string.
Each time someone copies, links and material into the system it will be automatically rated for virulence... But i don't have idea for the mathematics of this thing... How exactly will the virulence increased for instance, the function is not yet designed.
Here's some Python code I have with a Django web app project...
I am showing the models.py file
virulence = None
word = VarChar(max_length=1024)
uri = VarChar(max_length=1024)
text = VarChar(max_length=4096)
rating = Int()
tags = OneToMany(Tag)
resources = OneToMany(Resource)
users = OneToMany(User)
pass # :)
I had also the idea of realizing the previous with a functional model under Haskell but am I real newbie there, so I started the project with Python and traditional OO. I will host the project on GitHub(http://github.com)