Psychological Bulletin · 1972 · 808 citations · 20 references
Social SciencesPsychologySocial PsychologyIndividual DifferencesPersonality PsychologyPsychometricsAttitude ChangeBiasSocial JudgmentAffectAttitude AmbivalenceAttitude MeasurementsAttitude PolarizationData ValidityIndifference RelationNegative AffectivitySemantic Differential Scale Development
Attitude research traditionally treats attitudes as unidimensional, favoring or disfavoring an object, but this article examines the ambivalence‑indifference problem and proposes a new measurement approach. The study proposes a modification of the semantic differential technique to separately measure liking and disliking components. The authors develop a geometrical model distinguishing total affect, ambivalence, and polarization as nondirectional variables within the modified semantic differential framework. Reliability and validity analyses confirm the model’s soundness, and an application example demonstrates its practical utility.
This article explores the alternate meanings of attitudinal neutrality in the context of the bipolarity-reciprocal antagonism issue. Specifically, it proposes a modification of the semantic differential technique wherein the liking and disliking components of can be separately measured. A geometrical model is developed in which three nondirectional variables (total affect, ambivalence, and polarization) are distinguished from the usual variable. Reliability and validity data are presented, and an application of the model is discussed. In his 1935 review of the general area of theory and research, Gordon Allport concluded that most investigators basically agreed that attitude is a learned predisposition to respond to an object in a consistently favorable or unfavorable manner [p. 818J. Furthermore, he suggested that this bipolarity in the direction of an (i.e., the favorable versus unfavorable) was viewed as its most distinctive feature. Thus, he felt that had been conceptualized as a simple unidimensional concept—the evaluative (or affec
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