Semantic Networks Flashcards
Hierarchical semantic network model
Node = category/concept
Ex: knowledge about robins is in your node for bird
Semantically related nodes are linked
Rosch’s 3 levels of concepts
Subordinate, basic, superodinate
Cognitive economy
Shared properties stored at higher-level nodes
Ex: robins can fly– robin is in bird node and being able to fly is connected with being a bird
Collins & Quillian’s model
Verifying properties should take longer the more nodes must be traversed (longer “distance”)
Canary can sing < canary can fly < canary has skin
“lexical decision” priming task
If spreading activation is real we should be able to see priming effects
Presented with pairs of word-like stimuli that are related or not related to each other
Faster when related in meaning than when not related in meaning
Spreading activation
When a concept is presented, relevant node is activated
Canary node is warmed up, so other related concepts are more easily accessed from memory
Priming!
We can infer how connected concepts are by reaction time
Criticisms of Collins & Quillian’s model
Cannot explain typicality effects
We’re faster to verify canary as a bird than ostrich, but they should be equal because distance is one node for both
Little evidence for cognitive economy
Some sentence-verification results are problematic
Ex: “pig is an animal” verified faster than “pig is a mammal” even though former distance is longer
Conceptual knowledge
knowledge that enables us to recognize objects and events and to make inferences about their properties
Wittgenstein’s family resemblance
problem that definitions often do not include all members of a category
Ex: chairs all somewhat look alike even if they’re different
Prototype
Typical member of a category
Exemplar approach
determining whether an object is similar to other objects
Ex: if a person has encountered sparrows, robins, and blue jays in the past, each of these would be an exemplar for the category “birds.”
