Semantic feature-comparison model: Difference between revisions

Revision as of 21:42, 13 November 2012

Revision as of 02:33, 20 November 2012

Line 1:

'''Semantic Feature Comparison Model''' is used “to derive predictions about categorization times in a situation where a subject must rapidly decide whether a test item is a member of a particular target category” (Smith et al, 1974, p. 215)[1]. When pressed with time, how do we make judgments and place items or events in particular categories? That is what the model tries to answer. As such, in this semantic model, there is an assumption that certain occurrences are categorized using its features or attributes of the two subjects that represent the part and the group. For example, which is often used to explain this model, the statement a ‘robin is a bird’. The meaning of the words robin and bird are stored in the memory by virtue of a list of features which can be used to ultimately define their categories, although the extent of their association with a particular category varies.

==History==

This model was conceptualized by Edward Smith, Edward Shoben and Lance Rips in 1974 after they derived various observations from semantic verification experiments conducted at the time. The task is simple: respondents merely have to answer ‘true’ or ‘false’ to given sentences. Out of these experiments, they observed that people respond faster when (1) statements are true, (2) nouns are members of smaller categories, (3) items are ‘typical’ or commonly associated with the category (also called prototypes), and (4) items are primed by a similar item previously given (University of Alaska Anchorage, n.d.), such as previous statement ‘eagle is a bird’ and next statement ‘robin is a bird’. In the latter item, respondents will respond faster to the latter statement since the category bird has been primed. So, based on the previous observations, the proponents were able to come up with the Semantic Feature Comparison Model.[1]

==Theory==

Line 16:

====Experiments====

Two separate experiments were conducted to support the model proposed by Smith, Shoben, & Rips, 1974. The first experiment tested category size in determining semantic decisions and the second experiment was called the Instance-Category Verification Experiment. In the first experiment, the effects of category size leading to an overall increase or decrease in the overall similarity for instance-category pairs was measured. Smith, Shoben, and Rips hypothesized that for each instance, the production frequency of the category was a measure of that categories overall semantic similarity to the instance. 30 young adults from Stanford University were the subjects in the study. The task began by selecting 26 triples ( instance plus two categories). The statement “An S is a P” is typed onto two different cards. One card for the instance and smaller category and the other card is for the instance and the larger category. All 52 true statements are randomized with 52 false statements by pairing instances and categories from different triples. The instance-category pairs were then presented individually to a subject for rapid verification.[2]

In the category size experiment, the Featural Model for Semantic Representation is also quantified where the value, x, is equal to the overall similarity between the instance and the target category. The x value determines whether the participants execute a fast reaction time in both true and false response. True responses are (x>c1) and False responses are (x<c1). When the participants are having a difficult time determining the similarity between the instance and the target category, (co<x<c1), the second stage of the semantic feature model is entered; which focuses more on the defining features of the instance and the target category. Four expressions where derived to quantify the probability of each error type and to express correct true and correct false reaction times.

In the second experiment, Subjects are presented a set of instance-category pairs. (Several instances were used for each category). Subjects rated typicality of each instance to its associated category. Each category served as a target category for a block of 24 trials (12 containing target instances & 12 containing non-target instances). The experiment initiated by selecting four categories and 12 target instances for each of these categories. Each category served as a target category for a block of 24 trials. Twelve of these trials presented the target instance while the other 12 did not. One block of 48 trials occurred in which the target was animal and a comparable block were plant were the target categories; the 24 target trials contained bird and insects as the instances and while the non-targets were the fruit and vegetable instances. The assignment of targets and non-targets in reversed in the plant block. A total of 6 blocks corresponded to the six possible target areas bird, insect, fruit, vegetable, and animal were conducted. These blocks were randomized and balanced across subjects. Target categories were given verbally at the start of each block and the test instances were presented visually for the subjects to rate as true or false in belonging to the target category.

Line 65:

==References==

[1]<Smith, E. E., Shoben. E. J., and Rips, L. J. (1974). Structure and Process in Semantic Memory: A Feature Model for Semantic Decisions. Psychological Review, 81(3), 214-241>

[2]<University of Alaska Anchorage (n.d.). Cognitive Psychology - Memory Models, Knowledge Representation. Retrieved November 5, 2012 from http://www.math.uaa.alaska.edu/~afkjm/cs405/handouts/psycho.pdf>

[3]<Gazzaniga, Michael S., Richard B. Ivry, and G. R. Mangun. "Methods of Cognitive Neuroscience." Cognitive neuroscience: the biology of the mind. Third ed. New York: W.W. Norton, 1998. 111-112. Print.>

[4]<Gazzaniga, Michael S., Richard B. Ivry, and G. R. Mangun. "Methods of Cognitive Neuroscience." Cognitive neuroscience: the biology of the mind. Third ed. New York: W.W. Norton, 1998. 112-114. Print.>