The Semantic Feature Model

To address some of the shortcomings of models like Collins and Quillian’s (1969), Smith and colleagues (1974) developed a model that viewed the meanings of words as sets of semantic features or attributes (Smith et al., 1974). These features can be broken down into two types: characteristic and defining. Defining features are ones that are essential to distinguishing a concept from others (their most salient feature), while characteristic features are ones that are not essential to this. For example, a defining feature of “robin” is that it is “red-breasted,” while a characteristic feature is that it is "small.” The more defining features concepts share, the closer together they are organized in the mental lexicon. Thus, looking at the defining features shared between “bird,” “robin,” and “ostrich,” we see that “robin” and “bird” share 3, while “ostrich and “bird” share 2, meaning that “robin” would be grouped closer to “bird” than “ostrich” (see Figure). A hierarchical model, by contrast, would organize “ostrich” and “robin” equally close to “bird.” Thus, this model allows for more flexibility and levels in connections between nodes (lexical entries). Another key aspect of this model is that the more concrete a concept is, the more defining features it has, and the easier it is to make a semantic decision about it when compared with another concept. For example, when performing a semantic categorization task, it is easier to make a decision about the question, “Is a dog a toaster?” than, “Is an animal a thinker?”