Advantages semantic differential
Theory suggests that the semantic differential is one of the most appropriate techniques to assess the intensity and direction of the meaning of concepts, opinions, and attitudes [1, 2]. The advantages of the semantic differential are also backed by empirical results. For instance, the semantic differential has been demonstrated to outperform Likert-based scaling or stapel scaling on robustness , reliability , and validity . In addition, the semantic differential has been demonstrated to function effectively as a short-form scale format to reduce survey completion time .
Next to the advantages referred to in the above, there is a linguistic advantage of the semantic differential worth mentioning. As depicted in the figure in the below, the core elements of a semantic differential include the concept to be measured, a negative polar, a positive polar, and a scale connecting both polars. The basic elements of the widely applied Likert-type scale on the other hand are a declarative statement and usually a generally accepted scale ranging from ‘strongly disagree’ to ‘strongly agree’ .
A unique benefit of the semantic differential is that it offers respondents the opportunity to express their opinions about the concept more fully, that is, ranging from the negative polar (e.g., ‘weak’, see the figure) to the positive polar (e.g., ‘strong’, see the figure). Converting the example semantic differential shown in the figure to a Likert-type scale measuring the same concept illustrates this benefit. In the case of the Likert-type scale, respondents can only indicate the extent to which they disagree or agree with a statement that typically consists of the concept and a description of the concept that corresponds with one of the two verbal opposites (e.g., ‘Concept X is strong’) [see 6]. A ‘strongly disagree’ on such a scale, however, does not automatically imply that a respondent sees the object as the opposite (‘being weak’). It only expresses the extent to which one’s view about the object aligns with the statement that goes with the rating options . As it is widely advocated that while thinking and communicating humans want to give both positive and negative information to indicate what they mean , usage of verbal opposites in a measurement instrument seems most natural to fully measure the perception of concepts, opinions and attitudes (also see ).
References used on this page:
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2. Osgood, C.E., Suci, G.J., and Tannenbaum, P.H. (1957) The measurement of meaning, University of Illinois Press, Urbana, IL
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6. Chin, W.W., Johnson, N. and Schwarts, A. (2008), A fast form approach to measuring technology acceptance and other constructs. MIS Quarterly 32(4), 687-704.
7. Netemeyer, R.G., Bearden, W.O., and Sharma, S. (2003), Scaling procedures: Issues and applications, Sage, Thousands Oaks, CA.
8. De Tré, G, Zadronzny, S. and Bronselaer, A.J. (2010), Handling bipolarity in elementary queries to possibilistic databases. IEEE Transactions on Fuzzy Systems 18(3), 599-612.