Visualizing a meme

I began to finish up the classification system I began to visualize a meme. Below is what I came up with.

• First thing that stands out is the square it represents the package of the meme. It contains the meme and delivers its to all the targets.
• Next are the targets and those are all the people who the meme is aimed at. They can be planned or  random. It is from the targets that the parts of the meme are developed.
• The interactions between the meme and the targets is the stickiness of the meme.
• Within in the package are the symbols, signs and signals that come together to form the message.

Here is the  OCW video that I developed this meme diagram.

http://front.moveon.org/the-most-powerful-occupywallstreet-clip-you-will-see-this-month/ 

I began to finish up the classification system I began to visualize a meme. Below is what I came up with.

• First thing that stands out is the square it representative the package of the meme. It contains the meme and delivers its to all the targets.
• Next are the targets and those are all the people who the meme is aimed at. They can be planned or they can just be random. It is from the targets that the parts of the meme are developed.
• The interactions between the meme and the targets is the stickiness of the meme.
• Within in the package are the symbols, signs and signals that come together to form the message.   

Beta Meme Classification Taxonomy 2.1

I have worked on the meme classification system and added a page so that we can track changes in the taxonomy.  Just go to the page if you are interested.  

SIR Model for Meme Propagation

I've been thinking about this idea for a while, and thank goodness I am not. Here is a good paper on the idea that the SIR model will work well to describe meme movements. The paper has this abstract:

We study the dynamics of information propagation in environments of low-overhead personal publishing, using a large collection of weblogs over time as our example domain. We characterize and model this collection at two levels. First, we present a macroscopic characterization of topic propagation through our corpus, formalizing the notion of long-running “chatter” topics consisting recursively of “spike” topics generated by outside world events, or more rarely, by resonances within the community. Second, we present a microscopic characterization of propagation from individual to individual, drawing on the theory of infectious diseases to model the flow. We propose, validate, and employ an algorithm to induce the underlying propagation network from a sequence of posts, and report on the results.