In a NutShell

The Word-Sensibility Model

We might imagine each word as representing a discrete dynamical system. All systems draw upon the environment and then give back to it, thus participating in an ecology of dynamical systems (i.e., Dynamical Context.)

Word-sensibility is about words operating like units of homeostasis. A word is like a sensing unit of homeostasis where it responds to changes presented to it in a text. It finds stasis by adjusting its coordinates on the x-y axes to coordinates that its zeropoint can most effectively anchor for.

  • For example, barrier is a changing dynamic FOR passage of topic-door.
  • Barrier represents potential coordinates. Passage is the zeropoint.
  • Each unit is a kind of reference frame in which the dynamic sense of a word is balanced to a context e.g., IF context a THEN more x less y.

Consider the contextual dynamics of door for the sentences below:

  • Context a: “Close the door because it’s cold outside.”
  • Context b: “Open the door because it’s hot in here.”
  • Quadranym: (x)  door(x) [Open(passage) Close(barrier)(x)]

In the example above, one might imagine how a statistical model can model a homeostasis regarding door and climate changes as well as, security, privacy and aesthetics (i.e., word-topics cluster inferential word vectors.)

Now imagine every word having its own kind of responsiveness.

From: Word-Sensibility: Model Introduction

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“I know nothing in the world that has as much power as a word. Sometimes I write one, and I look at it, until it begins to shine.”

Emily Dickinson