mytest > help > Part 2. MM4XL Tools > 3. Charts and Maps > Semantic Differential > Technicalities: The semantic differential concept

Semantic Differential

Technicalities: The semantic differential concept

People adopt attitudes, hold opinions and express emotions with varying levels of intensity. To investigate attitude and measure its intensity, investigators typically use rating scales. Psychologists Thurstone and Likert pioneered attitude-measurement scaling methodologies with a type of differentiated scale: a scale that would determine with acceptable accuracy a persons attitude (towards an object or concept) along a continuum. Likert, who also had great interest in corporate management, devised a summated attitude scale that allowed for the summation and averaging of scaled responses. It follows an example of a Likert scale.

  • Strongly agree
  • Somewhat agree
  • Neither agree nor disagree
  • Somewhat disagree
  • Strongly disagree

There are many variations on this theme, but in general, Likerts method involved attaching numbers to levels of meaning. The Likert-type scale proved to be extremely robust, and continues to be widely used today.

The scale types devised by Thurstone, Likert, and others, however, did not connect measurement with the meanings of words. Charles Osgood in the early 1950s constructed a bipolar scale based on semantic opposites, such as "good-bad", "soft-hard", "fast-slow," "clean-dirty," "valuable-worthless," "fair-unfair," and so on. Osgood called these scales "semantic differential" scales because they differentiated attitudinal intensity based on a persons subjective understanding of the connotative meanings of words.

Osgood et al. explored large amounts of attitudes on numerous words and phrases. The outcome was Osgoods discovery of "semantic space"the existence of three measurable underlying attitudinal dimensions that everyone uses to evaluate everything in their social environment, regardless of language or culture. These three dimensions are Evaluation, Power, and Activity, known as EPA.

The semantic differential is a method for measuring the meaning of an object to an individual. It may also be thought of as a series of attitude scales. The subject is asked to rate a given concept (for example, Irish, Republican, wife, me as I am) on a series of seven-point bipolar rating scales. Any conceptwhether it is a political issue, a person, an institution, a work of artcan be rated . . . Subgroups of the scales can be summed up to yield scores that are interpreted as indicating the individuals position on three underlying dimensions of attitude toward the object being rated. These dimensions have been identified by using factor-analytic procedures (factor analysis is a [statistical] method of finding the common element or elements that underlie a set of measures) in examining the responses of many individuals concerning many concepts or objects. It has been found that . . . three subgroups measure the following three dimensions of attitude: (1) the individuals evaluation of the object or concept being rated, corresponding to the favorable-unfavorable dimension in more traditional attitude scales; (2) the individuals perception of the potency or power of the object or concept; and (3) the individuals perception of the activity of the object or concept.

(Kidder, 1981)

Of the three dimensions of semantic space, Evaluation proved to be the most important. Evaluation is also known as the connotative or affective dimension. Affective or affect is the term psychologists use when referring to emotion, or more specifically, the emotion associated with an idea or set of ideas.

The problem with the semantic differential technique is that it does not distinguish beyond a single evaluative continuum, with positive attitude at one end of the scale through to negative attitude at the other end. That is, it does not actually identify any individual emotions.

Lifetime license:
MM4XL All Tools
Price: euro 238.00

Vote this tool
149 votes: vote vote vote vote vote
5 stars:
65
4 stars:
79
3 stars:
3
2 stars:
1
1 star:
1
We proudly serve
Your vote
vote1 vote2 vote3 vote4 vote5
Email:
Gender:
M
F
Age:
Position:
Department:
Comment: