Patterns of mood change

Howarth, Edgar; Young, Paul David

doi:10.1016/0191-8869(86)90002-4

Cited by 9 publications

(5 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Representative emotions were arranged in a circle, as shown in Figure . Other studies found similar circular patterns of emotions in a two‐dimensional space with minor variations of this configuration …”

Section: Introductionsupporting

confidence: 64%

See 1 more Smart Citation

Correspondence analysis of color–emotion associations

Hanada

2017

Color Research & Application

117

View full text Add to dashboard Cite

Emotions are often associated with colors, but what mediates color-emotion associations is not fully understood. This study examined associations between colors and emotions using correspondence analysis. The hypothesis that emotions are associated with colors through the correspondence between the hue circle and the circumplex model of emotion/affect was tested. Participants viewed 40 colors and reported a word that expressed an emotion that they associated with or felt in response to each color. Participants' responses were aggregated into a contingency table of colors and emotion words, and a correspondence analysis was conducted. An eight-dimensional biplot was obtained. The first and second dimensions were related to hue, and the hue configuration was similar to colors' spectral trajectory in the CIE xy space or the CIELAB a*b* color space. The configuration of emotions was not consistent with the circumplex model of emotion, which rejected the above hypothesis. The associations in dimensions 1 and 2 appeared to be mediated by the perceived temperature of colors and emotions. In dimensions 3-6, dimensions that seemed to reflect secondary associations based on cultural convention or personal experiences (such as white with emotionless and purity and blue with depression) were obtained. These results also demonstrated the usefulness of correspondence analysis for analyzing color-emotion associations due to its ability to reveal the underlying statistical structure of associations. K E Y W O R D Scolor, correspondence analysis, emotion

show abstract

Section: Introductionsupporting

confidence: 64%

“…Other studies found similar circular patterns of emotions in a two-dimensional space with minor variations of this configuration. [42][43][44][45] Thus, hues and emotions can be represented as a circle in a two-dimensional space. Here, we hypothesize that emotions are associated with colors by matching the hue and emotion circles.…”

Section: Introductionmentioning

confidence: 99%

Correspondence analysis of color–emotion associations

Hanada

2017

Color Research & Application

117

View full text Add to dashboard Cite

show abstract

“…Thus, our analyses were based on 47 correlation matrices drawn from 14 articles (Borgatta, 1961; Diener, Smith, & Fujita, 1995; Feldman, 1995b; Feldman Barrett, 1996; D. P. Green et al, 1993; Howarth & Young, 1986; Kercher, 1992; Mayer & Gaschke, 1988; Mayer, Mamberg, & Volanth, 1988; Russell & Mehrabian, 1977; Russell & Pratt, 1980; Rusting & Larsen, 1995; Sjoberg et al, 1979; Watson, 1988).…”

Section: Methodsmentioning

confidence: 99%

“…Substantial evidence has accumulated that is consistent with this model of affect. Principal-components analyses of self-reported affect and multidimensional-scaling analyses of similarity judgments of affective states have suggested that affective states form a circular pattern in two-dimensional space (e.g., Block, 1957; Bush, 1973; Feldman, 1995a, 1995b; Feldman Barrett & Russell, 1998; Howarth & Young, 1986; Meyer & Shack, 1989; Russell, 1978, 1980; Russell & Mehrabian, 1977; Russell & Pratt, 1980; Russell & Steiger, 1982; Rusting & Larsen, 1995; Watson & Tellegen, 1985; Zevon & Tellegen, 1982). Analyses of judgments of facial expressions of emotion have also suggested a circular structure (e.g., Abelson & Sermat, 1962; Cliff & Young, 1968; Dittmann, 1972; Fillenbaum & Rapoport, 1971; R.…”

mentioning

confidence: 99%

Reexamining the circumplex model of affect.

Remington,

Fabrigar,

Visser

2000

Journal of Personality and Social Psychology

240

169

View full text Add to dashboard Cite

The circumplex model of affect has been among the most widely studied representations of affect. Despite the considerable evidence cited in support of it, methods typically used to evaluate the model have substantial limitations. In this article, the authors attempt to correct past limitations by using a covariance structure model specifically designed to assess circumplex structure. This model was fit to 47 individual correlation matrices from published data sets. Analyses revealed that model fit was typically acceptable and that opposing affective states usually demonstrated strong negative correlations with one another. However, analyses also indicated substantial variability in both model fit and correlations among opposing affective states and suggested several characteristics of studies that partially accounted for this variability. Detailed examination of the locations of affective states for 10 of the correlation matrices with relatively optimal characteristics provided mixed support for the model.

show abstract

“…The second approach involves investigating the relationship between mood variability and established personality, ability and motivational factors (e.g. Cooper & McConville, 19896;Howarth, 1988). If it proved possible to accurately predict mood variability from a combination of standard tests, such estimates could be used to interpret the significance of mood scores.…”

Section: Minimizing the Influence Of Mood Variability On Mood Levelmentioning

confidence: 99%

Interpreting mood scores: Clinical implications of individual differences in mood variability

Cooper

McConville

1990

British Journal of Medical Psychology

View full text Add to dashboard Cite

Mood variability is shown to be a stable characteristic of individuals, such individual differences accounting for some 25 per cent of the total variability of mood scores over time. This large effect is shown to have three major consequences: it is impossible to use tables of norms to assess the severity of a given mood for an individual; the whole logic of using norms for the interpretation of moods is flawed; and correlations between moods and traits have been underestimated in the literature. Various techniques are discussed for minimizing the effects of bias caused by individual differences in mood variability.

show abstract

Patterns of mood change

Cited by 9 publications

References 21 publications

Correspondence analysis of color–emotion associations

Correspondence analysis of color–emotion associations

Reexamining the circumplex model of affect.

Interpreting mood scores: Clinical implications of individual differences in mood variability

Contact Info

Product

Resources

About