Semantic Network Theory

The Semantic Network Theory is a cognitive model that aims to explain how humans organize and process information in their minds. This theory suggests that knowledge is represented in the form of interconnected nodes or concepts, forming a semantic network.

Concepts

In Semantic Network Theory, concepts are the fundamental units of knowledge representation. They represent ideas, objects, or events that are linked together based on their semantic relatedness. Concepts can vary in their level of abstraction and can be organized into hierarchical or non-hierarchical structures.

Nodes

Nodes in a semantic network represent individual concepts or ideas. They are connected to other nodes via links or associations, forming a network of interconnected knowledge. Each node contains information about a concept, including its attributes, properties, and relationships with other nodes.

Links

Links are the connections between nodes in a semantic network. They represent the relationships or associations between concepts. Links can be labeled to indicate the type of relation, such as “is-a,” “part-of,” “causes,” “belongs-to,” or “is-related-to.” The strength and directionality of links may vary, indicating the strength or importance of the relationship between concepts.

Activation

In a semantic network, the activation of a node refers to its level of accessibility or availability for processing. Nodes can become activated through various processes, such as direct experience, attention, or retrieval cues. Activated nodes can then activate related nodes, facilitating the spreading of activation within the network.

Priming

Priming is a phenomenon in semantic network theory where the activation of one concept facilitates the activation of related or associated concepts. When a concept is primed, it becomes more accessible and retrieval of information related to that concept becomes easier, compared to non-primed concepts.

Schema

Schemas are higher-level knowledge structures that organize and guide the processing of information in semantic networks. Schemas are generalized frameworks that represent knowledge about a particular concept or domain. They help in capturing the essential characteristics and relationships within a semantic network.

Applications

The Semantic Network Theory has been used in various fields, including psychology, linguistics, artificial intelligence, and information retrieval. It provides insights into how humans understand and retrieve information, aiding in the development of computational models, language processing techniques, and improved information organization systems.