Language Entropy

The text explores the relationship between language, abstraction, and complexity in written communication, particularly in research papers. It introduces key concepts such as abstractness, entropy, and understanding. Abstractness is defined as the distance of a word's definition from tangible objects, while entropy measures randomness and uncertainty. The author posits that more abstract words lead to lower entropy, allowing for denser information in fewer words. This efficiency is likened to a form of compression, where the reader's prior knowledge fills in gaps left by the writer. The complexity of text is influenced by its total abstraction and entropy, with a higher number of abstract words indicating greater complexity. The discussion also touches on word embeddings and their role in quantifying these concepts through mathematical functions. The author emphasizes that complexity is relative to the reader's knowledge base, which also has its own entropy. Ultimately, the piece reflects on the interplay between formalism in language and the realism it seeks to convey.

- The relationship between abstractness and entropy affects the density of information in text.

- More abstract words result in lower entropy, leading to more efficient communication.

- Complexity in text is influenced by the reader's prior knowledge and familiarity with concepts.

- Word embeddings can be used to quantify abstractness and entropy mathematically.

- Understanding of language is a cumulative process, enhancing comprehension over time.