Context is a rabbit hole, and I am NOT Elmer Fudd. I caught the Rabbit.
It wasn’t easy. The problem started when I actually had to figure out what Context is rather than what it does. It’s complicated.
As a tool, Context is like a hammer. You use it but you don’t ponder much about it. But it’s a shifty, enigmatic thing, like a hammer the first time you see it that becomes a vase of flowers after you blink
BI limiting Context to my project & the problem of identifying Story Narratives in a website, I figured it out. Here is a few things about Context:
- You can impose your own context, like writing a business meeting Agenda. Or it can emerge from a conversation that goes from meandering to fix on a compelling point. I call this Deterministic & Incidental context.
- A single tag often has multiple meanings, Data Scientists call that Ambiguous. Joining it with a related tag narrows the meaning, eventually resolving it to one, what Data Scientists call Disabmbiguation.
- 2 ore more tags are related when they occur in more than one post. I call this The Story Principle.
- 2 or more related tags are a Context. Sometimes, I call that group of tags a Storyline.
- A group of 2-4 tags suggest a thing. More than that suggest multiple things. Many multiple things. A group of tags may hold many clusters of tags. This is Convergence and divergence, Clustering.
- Tags in one post join many different tags in many other posts. There could be hundreds of clusters in even a small web-site. I call this Proliferation though some would argue it’s Polymorphy.
- Tags are promiscuous, combining, conflating, comingling with each other. Each tag has many facets, many faces. Tags & clusters of tags are Polymorphic. This means yuo need multiple tags to resolve to a clear context.
- We have explicit context, a structure of nested tags, but we also have implicit context. You may see Apple, Orange as fruit, but implicit to this website, they are a Context example. The venue as another context as opposed to the one in your mind is a Scope.
- You can have multiple contexts, nested within each other in some order. Data Science calls this rule of order a Schema. This is a hierarchy but could also be a Breadcrumb or Branch of a tree, or a Chain.
- There is no fixed order, or scheme for nested, hierarchical contexts. Whether you manually build one or whether an algorithm uses a clever method to do so. The last point is why nobody can just build a huge tree of Everything even if we have the capability. Nobody can agree on the Schema.
- I use tag weights, how manyposts they occur in as the means of consistently ordering groups of tags. Honestly, this is a very weak justification & results in novel & interesting juxtapositions of concepts, but it is a consistent, understandable way to create these hierarchies.