Co-word Analysis
Updated 2026-08-10
INTRODUCTION
English translation pending.
CORE DEFINITION
A bibliometric method that counts keyword co-occurrences within documents and builds an association network from them. The core proposition is that keywords appearing in the same document indicate a semantic relationship, so the network of co-occurrences constitutes a navigable map of a knowledge domain. The key qualification is that co-occurrence frequency is not importance and not causation, and the choice of time window materially changes the conclusions.
SCAFFOLDING EFFECT
Reduce cognitive load
- Keyword extraction: pull the terms the field actually uses from the corpus. - Network mapping: build the co-occurrence matrix and normalize association strength. - Evolution tracking: compare networks across time periods to see themes rise and fall.
Anchor fast decisions
Authors select keywords that describe the content of a paper, so two terms appearing in the same paper are likely to be conceptually linked in the author's framing. Aggregating across a corpus converts these individual selections into a frequency-based graph, where dense clusters correspond to established themes and shifting links indicate emerging ones. The map summarizes collective labeling behavior rather than truth.
MINIMUM ACTION
In progress 0/1Practice this model in one real situation:
account_treeGenealogyexpand_more
menu_bookReferencesexpand_more
Source support: Explicit
- en.wikipedia.orghttps://en.wikipedia.org/wiki/Co-occurrence_networkverified
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