The more I think and write on this subject the more I am drawn to the conclusion, that a classification system for memes needs to be developed. Without it SMiSC can neither spot a meme attack, defended against one or develop its own meme attack. Simultaneously a definition of meme will also need to be developed.
There are many ways to classify something. In the purest sense classification is the organization of knowledge (memes's) into a systematic order. Most systems are hierarchical, dividing the knowledge into categories and subcategories consisting of: facets, or characteristics of something in our case memes, arrays or links of facets horizontally and the chains the vertical connects of facets.
Modern classification schemes focus on facet analysis and synthesis. That is the breaking up and reassembling so as to identify the basic related facets (Chan: 1994 p. 259-261).
While these general principals come from information science, they hold true for most systems, however, when discussing memes most people would tend to think more of the biology taxonomies. The main reason is that the two approaches to memes whether genetics or viral are biological. I ll not bore you with the history of the approach but to say the modern system is known as the evolution. Here the lead facet and first array is called Kingdoms with chains known: as phylum, class, order, family, genus, and last species. This system is extremely complex and often experience great upheavals: either by designers seeking to streamline or order the system or because something new is discovered such as the recent discovered A. Sediba which will reorganize the chain Homo. (Biological classification accessed September 12, 2011)
With this is mind SMiSC needs to be thought of in terms of arrays and chains. Take for example the first array might be seen as Culture with facets of: Political, Religious, Business, Race. The next chain of arrays could then be Geography lets say by country. A final chain could be made of facets of approach such as: humor, patriotic, academic, news. Naturally the real classification would include clear definitions to guide the process.
Now lets look at an example of a meme. “Pollocks are stupid” often carried in the joke “How do you sink a Polish submarine?...open the screen door.” The meme could be classified as follows.
Culture: Race
Geography: Poland
Approach: Humor
This also works when it comes from building a meme as required by SMiSC. First a mission or meme idea would be developed: embarrass a foreign leader. With the classification system in place we could begin from the bottom and work up. Starting with a fake news story, then pick the geography in this case the country the target is from, and finally what type of story a business one.
Leader A from country Y has secretly order all his accounts moved to Switzerland as rioters break into banks.
Regardless of what system is developed the more memes that are classified the smoother SMiSC projects will work. The system could than plugged into a GUI that would be added to systems that identify, track build and launch of memes.
"Biological Classification" http://en.wikipedia.org/wiki/Biological_classification accessed September 12, 2011
Chan, Lois Mae. (1994) Cataloging and Classification. McGraw Hill NY, NY.
I was thinking that maybe we need to define an arbitrary first stab at meme taxonomy and see about building a simple keyword-based classifier, or maybe a theme-based classifier based on neural net "theme recovery" techniques. We could shove a bunch of our own SMiSC articles through it. ;-) or our own texts from other writing.
ReplyDeleteWhile I believe your right it does take some work. I ll get back to you when I am reading.
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