Explanation
Complexity is not a single property measured identically across domains. Depending on the question, relevant dimensions may include the number and diversity of parts, their relationships, processing demands or description length. A linguistic system may be complex by one measure and simple by another. Claims about complexity must therefore specify their object, units and comparison procedure. Numerous parts alone establish neither difficult processing nor emergent behaviour. Randomness likewise cannot generally be equated with complexity. The term becomes analytically useful when a study replaces an overall impression with a justified and testable measurement decision.
Movement of thought
1. Identify the object. 2. Choose a relevant dimension of complexity. 3. Operationalise the measure. 4. Compare cases under equivalent conditions. 5. State the limits of the inference.
Scientific use case
A study can measure structure and reading times separately before testing their relationship.
Example
Two sentences with the same word count may have different embedding depths. Length and embedding capture different properties.
Counterexample
A longer sentence is not invariably harder to understand: familiarity and prior knowledge may affect processing.
Distinction
Distinguish complexity from length, difficulty, randomness and emergence.
Effect on thought and perception
Explicit measures make comparisons assessable.
Resonance
What seems intricate may display a simple order when approached with a different question.
Provenance
Parallel corpus 98f0950771ae4662f291d2f15f5c51b6797f3c20ba458a68615cdb177002ea18; case-bounded source review accepted; human specialist review not claimed.
Cite this entry
Reich, Michael (Hrsg./ed.): „Complexity“. Atlas der Sprache, AT-NAV-G03-039. ATLAS 259, data model 1.6.0. https://atlasoflanguage.com/concept/AT-NAV-G03-039The address remains stable; editorial content may evolve. Editorial reading state: 2026-10-15. Include your access date for precise references.