The Preponderance of Negative Emotion Words in the Emotion Lexicon

The Preponderance of Negative Emotion Words in the Emotion Lexicon: A Cross-generational and Cross-linguistic Study Robert W. Schrauf and Julia Sanchez Buehler Center on Aging, Northwestern University, Chicago, IL, USA The ‘working emotion vocabulary’ typically shows a preponderance of words for negative emotions (50%) over positive (30%) and neutral (20%) emotions. The theory of affect-as-information suggests that negative emotions signal problems or threat in the environment and are accompanied by detailed and systematic cognitive processing, while positive emotions signal a safe or benign environment and are accompanied by heuristic, schema-based cognitive processing. Further, the developmental theory of affect-complexity suggests that the ability to coordinate and manage complex emotions develops over the lifespan. More complex interpretation and reasoning about negative experience versus positive experience predicts that negative emotion labels will predominate in the emotion lexicon. The growth of affect-complexity over time predicts that the greater proportion of negative labels will remain constant for both young and older individuals. By asking monolingual Spanish-speakers in Mexico and monolingual English-speakers in the USA to make free-lists of as many emotions as they could in two minutes, we confirmed each of these predictions about the working emotion lexicon. Moreover, data from both languages showed the same proportional distribution, suggesting that the cognitive constraints on emotion processing and lexification may be cross-culturally invariant. Keywords: affect, emotion lexicon, aging, Spanish, English

This study adopts two current, related, psychological theories of emotional functioning and makes a series of predictions about the working emotion vocabularies of two language groups: Mexican speakers of Spanish and US speakers of English. The first theory, affect-as-information , argues that negative emotional experience triggers a distinct, more elaborated and detailed style of cognitive interpretation of experience, whereas positive experience triggers more general, schema and script-based cognitive processing (Bless et al ., 1999; Schwarz, 1990; Schwarz & Bless, 1991; Schwarz & Clore, 1983). The second theory, affect-complexity, is a developmental version of the first theory and argues that as individuals grow from youth into adulthood, they acquire greater facility in this detailed style of cognitive interpretation and coordination of both positive and negative emotional experience (Labouvie-Vief & Medler, 2002). In addition to these two theories, we make the assumption that detailed cognitive processing results in the generation of distinct labels for mental and emotional phenomena. That is, the more individuals think about something, the more distinctions they will make, and the more words they will use to hold these distinctions in mind. 0143-4632/04/02 266-19 $20.00/0 – 2004 R.W. Schrauf & J. Sanchez J. OF MULTILINGUAL AND MULTICULTURAL DEVELOPMENT Vol. 25, No. 2&3, 2004

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The Preponderance of Negative Emotion Words in the Emotion Lexicon

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Based on the two psychological theories and the assumption above, we predict that (1) people have more negative emotion labels available to them at any one time than positive emotion labels. Put simply, people know more words for negative emotions than positive emotions. Note that this is a fact about the ‘working emotion vocabulary’ and not about entire languages. Furthermore, as a result of the accumulation of emotion experience and the cognitive processes of attending to it, interpreting it and managing it, we predict that (2) older people will have more diverse emotion vocabularies than young people. However, since we have no principled reason to assume that older people have proportionally more negative experiences than younger people, we predict that (3) the greater proportion of negative labels (due to more elaborated cognitive processing) versus positive emotion labels remains the same for older and younger people. Finally, we test these predictions about the emotion lexicon among monolingual Spanish speakers and monolingual English speakers. Because we assume that the cognitive mechanisms described above do not differ from culture to culture, we predict (4) no differences between the languages in the distributions of negative and positive terms. The study is therefore focused on the emotion vocabulary and not on emotion itself. Nevertheless, some specification is necessary as to what counts as an emotion. Thus, we took an empirical approach to deriving participants’ working emotion lexicons by asking them to free-list as many emotions as they could in a two-minute period. Some of the labels they produced seemed intuitively emotion-like (e.g. love, happiness), other terms seemed less so (e.g. doubt). We adopted some consensus positions from the literature (Izard, 1993) to make decisions in this regard. That is, emotion labels had to refer to some neurophysiological (‘bodily’) state, accompanied by an experiential component (‘a feeling’), and be distinct from purely cognitive states.

The Affect-as-information Theory In one sense, emotions are complex physiological-affective-cognitive responses to the physical and sociocultural environment. Recent research suggests that positive and negative emotions constitute two separate channels of evaluative processing. One channel is sensitive to what is safe and/or desirable, while the other is attuned to threat-related negative information (Cacioppo et al ., 1998; Cacioppo & Gardner, 1999; Watson & Clark, 1992; Zautra et al ., 1997). Although at the level of response, positive and negative emotions may appear to represent opposite poles on one continuum, the behavioural and neurophysiological evidence suggests that they are in fact separately processed. By extension, the theory of affect-as-information holds that positive emotions act as signals that the environment is basically benign; negative emotions signal that some problem or threat is at hand (Schwarz, 1990; Schwarz & Bless, 1991; Schwarz & Clore, 1983). The cognitive responses to these two types of signals differ accordingly. Positive emotions trigger top-down, heuristic processing in which an individual relies on general knowledge structures (e.g. scripts) to interpret experience. Negative emotions trigger bottom-up, systematic processing in

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which an individual engages in more fine-grained, detailed analysis of experience. In a series of experiments with college students in both the USA and Germany, Bless and associates (1999) used mood induction techniques to stimulate happy versus sad moods in participants, played audio- and videotaped stories to them, and then engaged them in a recognition task to test for memory of details from the stories. Recognition was tested for scriptconsistent (typical) details, script-inconsistent (atypical) details, and unrelated details, half of which were actually presented in the stories and half of which were made-up (foils). ‘Happy’ participants were more likely than ‘sad’ participants to mistakenly ‘recognise’ made-up details that were scriptconsistent (typical) but that were not presented in the original stories, suggesting that when making recognition decisions they were relying more on their scripts rather than actual memories. Contrariwise, both happy and sad groups accurately remembered actually presented script-inconsistent (atypical) details and rejected made-up, non-presented atypical details, suggesting that mood had not affected the original encoding of details nor the ability to retrieve details from memory. In sum, positive emotions triggered more script-based, heuristic processing, whereas negative emotions triggered more detail-oriented, systematic processing.

The Affect-complexity Theory The management of emotion and cognitive response is a developmental task involving particular mechanisms of emotion regulation. Labouvie-Vief and Medler (2002) have recently examined two such mechanisms with different age-related effects. On the one hand, affect optimisation describes the ‘ability to dampen negative and maximize positive affect’ (p. 571), a mechanism which may account for much of the resiliency of older adults. That is, older adults often maintain a sense of positive outlook despite the physical, psychological and social losses often associated with aging (Carstensen, 1995; Diener et al ., 1991; Staudinger et al ., 1995). (This is the ‘paradox of well-being’.) On the other hand, affect complexity describes ‘the ability to coordinate positive and negative affect into flexible and differentiated structures’ (p. 571). This ability develops over time: ‘. . .as complex executive cognitive structures mature, individuals are better able to coordinate positive and negative feelings through processes of inhibition /disinhibition, evaluation, analysis, and so on’ (p. 571). Affect-complexity entrains a tendency toward an analytic and more systematic processing of experience, a process that may emphasise negative affect more than positive. The balance and growth of these two mechanisms of emotion regulation differ over the lifespan. In a cross-sectional study of young (15 /29), middleaged (30 /59) and older (60 /86) individuals from low, middle and high socioeconomic status (SES) backgrounds from Midwestern communities in the USA, Labouvie-Vief and Medler (2002) found that young adults showed low affect complexity and low positive affect, middle-aged adults showed both high affect complexity as well as high positivity, while older adults scored higher on positive affect than middle-aged adults but lower on affect complexity. The authors comment, however, that ‘. . .the differences between


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the middle-aged and older age groups were relatively minor’ while ‘. . .the younger adults were clearly set off from the oldest age group, which was qualitatively similar to the middle-aged group’ (p. 583). In sum, young people show lower levels of integration of negative and positive emotion and lower levels of positive affect in general, while older individuals show the opposite pattern: higher levels of valence integration and higher levels of positive affect in general.

The Imbalance of Negative Versus Positive Terms in the Emotion Lexicon These differences in the cognition of positive versus negative emotion predict differences in lexification in general and age-effects in particular. That is, in general, if negative emotions occasion more detailed cognitive processing, it would not be surprising if more ‘names’ were available for negative versus positive emotions, on the supposition that over time meaningful distinctions acquire labels. It is important to note here that this does not imply that people have more negative emotional experience than positive emotional experience. In fact, the mechanism of affect-optimisation describes the preference for the opposite. Rather, the issue concerns the styles of cognitive processing attendant on these differently valenced experiences. Hypothetically, a person with equal amounts of positive and negative experience would do more detailed and systematic thinking about negative experience than positive experience and ultimately require more labels to think through and interpret negative experience. Therefore a first hypothesis in this study is that the active working emotion vocabulary will have more negative than positive emotion terms.

The Working Emotion Vocabulary It is important to note here that we are not making an argument about languages themselves. That is, we do not assess the absolute number of negative versus positive emotion labels possessed by any one language (by counting them in a dictionary, for example), rather we are interested in the working emotion vocabulary. The working emotion vocabulary comprises those emotion labels immediately available to individuals as they think through their experience. In an absolute sense, languages differ in the size and range of their emotion vocabularies. In a review of the cross-cultural literature on emotion lexicons, Russell (1991) cited work that reported 2000 emotion words in English (Wallace & Carson, 1973), 1501 in Dutch (Hoekstra, 1986), and 750 emotion words in Taiwanese Chinese (Boucher, 1979). Recently, Church and associates (1998) reported 256 emotion labels in Tagalog (Filipino) by assembling a long list of 2991 potential trait and state adjectives (Church et al ., 1996) and then having trained and lay judges categorise the words as personality descriptors, emotion words or neither. Such work requires careful specification of what constitutes an emotion word (Clore et al ., 1987), and such definitions may differ from study to study. Storm and Storm (1987), for instance, found only

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577 English emotion words versus the 2000 suggested by Wallace and Carson (1973). More importantly, it is not clear to what extent any individual speaker of a language may be expected to know the entire lexicon. Thus, while Wallace and Carson reported 2000 English emotion words, they suggested that only 10% of these could reasonably be found in the working vocabulary of the average English speaker. This suggests that there is a useful distinction to be made between the ‘linguistic’ characterisation of the size and range of a culture’s emotion lexicon in an absolute sense and the ‘psychological’ characterisation of the lexicon in the sense of ‘working vocabulary.’ The former is an absolute fact about the language independent of its actual speakers at any one moment. It is a statement about a language’s historical accumulation of distinct words and range of nuance. The latter is an empirical finding culled from specific speakers of the language in some particular time and place. It is a statement about the psychological salience of the emotion vocabulary-in-common-use. These considerations concerning the cross-cultural variability of emotion lexicons lead to the following strategies in this study. The working vocabulary of emotion labels is operationalised here as the set of psychologically salient emotion words to which an individual has immediate access when asked to make a list of emotion words outside of any particular emotionally charged situation. Such lists are not a random sample of an individual’s entire emotion lexicon as differing emotional contexts could conceivably trigger words that remain unavailable during the listing exercise. Rather, these lists reflect the constraints imposed by the cognitive processes of searching long-term memory for words belonging to a particular category. (Interestingly, in fact there is research suggesting that emotion words are represented in memory in different ways from other word types, such as abstract or concrete words; Altarriba & Bauer, 2004). Presumably words that are most frequently used or that have most recently been used will enjoy higher activation and are more likely to be retrieved. In this sense, asking many individuals to make short lists of emotion words should generate words that are particularly culturally salient at the level of the group. Furthermore, at the level of the individual, words mentioned first on participants’ lists should also enjoy higher levels of activation than words mentioned last, and thus also be more psychologically salient. The exercise of free-listing thus provides a window onto the working emotion lexicon by focusing on labels that are immediately accessible to participants. Free-listing also gives a method for gauging the psychocultural salience of items by assessing the frequency of items across participants and the ranking (ordering) of items within participants.

The Emotion Lexicon of Younger Versus Older Adults Presumably it is also the case that, as individuals accumulate emotional experience over the lifespan, their active emotion vocabularies may be expected to change as well. The theories we have reviewed suggest two age-related effects on the emotion lexicon. Again, Labouvie-Vief and Medler (2002) found that young adults showed low affect-optimisation and low


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affect-complexity while older adults were higher on both. Thus, as a result of increased affect-complexity (the coordination of positive and negative feelings through processes of inhibition /disinhibition, evaluation, analysis and so on) among the older group, we would expect older adults to have a more diverse emotion vocabulary than young adults. Nevertheless, given that negative experience would trigger more detailed cognitive processing, we would still expect that both young and older adults would possess more negative than positive emotion labels. Further, since we have no principled reason to assume that older adults have more numerous negative versus positive experiences than do young adults, we predict that the relative proportions of positive versus negative labels would not change over the lifespan. Negative emotion labels will predominate in both young and old adults’ lexicons.

Cross-linguistic Similarities in Proportions of Negative Versus Positive Emotion Labels Finally, the affect-as-information and affect-complexity theories that drive our predictions about young people’s versus older people’s emotion lexicons have been developed in English samples, drawing on a variety of ages and socioeconomic backgrounds (e.g. Labouvie-Vief & Medler, 2002), and in German samples, drawing on student populations (e.g. Bless et al., 1999). If the structure of emotion as signal and the differential cognitive processing triggered by these signals (depending on whether the emotions are negative or positive) are either biologically universal or pancultural, we might expect that cultural differences will not affect our predictions about the preponderance of negative emotion labels over positive ones. Alternatively, were we to find that the working emotion vocabularies of individuals from a particular culture did in fact have more positive labels than negative labels, we would be obliged to reconsider either the emotion theories or the linguistic assumption concerning lexification. In this study, we test our predictions and make comparisons about the working emotion vocabularies of young and older Spanish speakers in Mexico City and young and older English speakers in the USA. At the level of the individual participants, taking into account each individual’s working emotion vocabulary, we again expect a preponderance of negative labels over positive labels and no differences between the groups. That is, we make the conservative assumption that there are no cultural differences in the fundamental functioning of emotions as signals about the environment and the differential cognitive processing attendant on negative versus positive signals.

The Present Study The following predictions are made. The theory of affect-as-information argues that negative emotions signal a problematic or threatening environment and trigger more detailed, systematic cognitive processing, whereas positive emotions signal a safe environment and trigger heuristic processing. The more detailed processing attendant on negative emotion suggests that more distinctions will be made among negative emotions and therefore predicts higher numbers of negative emotion labels relative to positive labels


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(Hypothesis 1). The theory of affect-complexity argues that as individuals grow from youth into adulthood, their ability to differentiate, inhibit, analyse and evaluate their emotional experience grows apace with their cognitive development. This increasing, systematic processing of both positive and negative emotions should drive greater lexification and predicts that older individuals will have richer emotion vocabularies than young people (Hypothesis 2). However, since we assume young people and older people have roughly equivalent numbers of positive and negative experiences, and since our theoretical commitment suggests more detailed processing of negative emotion, we predict that young and older people will not differ in having proportionally more negative than positive emotion terms in their vocabularies (Hypothesis 3). Finally, we test these predictions crosslinguistically among young and old monolingual Spanish speakers in Mexico City and monolingual English speakers in the USA, and we predict no differences between the languages on the preponderance of negative versus positive emotion labels (Hypothesis 4). Research design The study design involves systematic within- and between-language comparisons made between young versus old monolingual speakers of Spanish and English. For this purpose, groups of 20 year olds and groups of 60/year olds were recruited from the urban areas of Mexico City and Chicago. Because the focus is on the psychologically salient working vocabulary of emotion labels, participants were asked to complete an unconstrained free-listing task that would tap highly or recently activated emotion labels in long-term memory.

Participants Table 1 displays the sample characteristics for the total sample (n /121) divided into four groups of approximately 30 members each, stratified by culture and age. Participants in the monolingual English-speaking groups were recruited from urban Chicago: younger individuals in their 20s from college campuses, older individuals over 60 years of age from area senior centres and newspaper advertisements. Participants in the monolingual Table 1 Sample characteristics Cultural group

Anglos

Mexicans

Age group

Gender

Age

Years of education

M

sd

M

sd

Young (n/30)

12M, 18F

21.20

(2.22)

14.25

(1.33)

Old (n/30)

16M, 14F

74.80

(4.39)

14.27

(3.09)

Young (n/31)

18M, 13F

22.55

(2.08)

14.16

(1.84)

Old (n/30)

20M, 10F

64.83

(6.19)

15.06

(3.88)


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Spanish-speaking group were recruited from Mexico City: younger individuals in their 20s from local colleges and universities, older individuals over 60 years of age, initially from a local school system where they were employed as teachers and then from their relatives and friends. Young Anglos were not significantly different in age from young Mexicans but older Anglos were significantly older than older Mexicans by approximately 10 years (t(58) /7.19, p B/0.001). Participants were highly educated with 14 15 / years of formal schooling, with no significant differences between the groups on this variable. All participants gave informed consent and were recruited in accord with the policies for the protection of Human Subjects of Northwestern University.

Task Participants engaged in a paper-and-pencil free-listing task in which they were asked to list as many emotion words as they could think of in a twominute period. After making the list, participants were asked to evaluate the valence of each emotion that they listed by indicating whether the emotion was unpleasant (1), neutral (2) or pleasant (3). Instructions in English and Spanish are included in the appendix. This task was part of a larger free-listing project in which individuals made lists for six domains (animals, illnesses, emotions, men’s work, women’s work and ways to lose money). Only results of the emotion data are reported in this paper.

Coding Across lists, lexical forms, which were morphological derivatives of the same word, were reduced to one form (i.e. ‘anger’ and ‘angry’ were both coded as ‘angry’). Within lists, where participants repeated the same word twice in the same list, the second mention was eliminated. Also within lists, words that seemed to be synonymous (e.g. ‘jealous’ and ‘envious’) were retained since, presumably, the participant listing the words saw some difference in them. Finally, as indicated in the introduction, we coded as emotion labels those words that referred to bodily instantiated states with some experiential component (‘feeling state’) that were not primarily cognitive in nature. Thus, we eliminated words such as: ‘questioning’, ‘curious’, ‘suspense’, ‘doubtful’ and ‘pensive’ (in English), and indeciso , incertidumbre, reflexioń and contemplacioń (in Spanish). In Spanish, religiosidad was also eliminated from one list because it seemed to name a series of beliefs and related behaviours instead of an emotion.

Results List length To facilitate group comparisons, it is important to establish that across all four groups there is general equivalence in knowledge of the semantic domain of emotions. List length is often used as an indicator of a participant’s knowledge of a domain (Brewer, 1995; Gatewood, 1984), so that individuals who produce many words in a particular domain are presumably more knowledgeable about that domain than individuals who produce very few.

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There were no significant differences in list-length across groups (young Anglos: M /10.03, sd/3.38; older Anglos: M /9.83, sd/4.10; young Mexicans: M /9.65, sd/3.80; older Mexicans: 8.53, sd /3.56). Therefore, any differences in the analyses that follow are not due to differences in word production. Equivalent length of lists across these four groups suggests similar knowledge levels of the domain of emotions. Consensus A related issue concerns the degree of agreement among individuals about what belongs in the emotion domain and what does not. Consensus analysis, which is a minimum residuals factor analysis of a data matrix (Borgatti, 1996; Romney et al ., 1986), is used to measure this agreement. A respondent-byemotion matrix was created for each group by entering a 1 into every cell where a participant mentioned an emotion and a 0 into cells for emotions that he or she did not mention, and then factor-analysing the matrix. By convention, where the first eigenvalue is three times as large as subsequent eigenvalues, cultural consensus is understood to exist in the group. This was the case for each of the four groups. For young Anglos, the first eigenvalue (17.36) accounted for 88.4% of the variance (second value: 1.37, 7%; third: 0.91, 4.5%). For old Anglos, the first eigenvalue (19.92) accounted for 92.9% of the total variance (second value: 0.927, 4.3%; third value: 0.587, 2.7%). For young Mexicans, the first eigenvalue (19.21) accounted for 91.0% of the total variance (second value: 1.12, 5.3%, third value: 0.77, 3.7%). For older Mexicans, the first eigenvalue (20.87) accounted for 95.2% of the total variance (second value: 0.573, 2.6%; third value: 0.477, 2.2%). These analyses point to high withingroup agreement that the words recalled constitute a coherent and bounded semantic domain. Measures of psychocultural salience Testing the hypotheses of the study requires the computation of the psychocultural salience of emotion labels. Salience refers to the importance, representativeness or prominence of items to individuals or to the group, and is measured in three ways: word frequency across lists, word rank within lists and a combination of these two, called Smith’s S (Smith, 1993). In terms of frequency, words mentioned by many people are taken to be more salient than words mentioned by one or two individuals (Bousefield & Barclay, 1950; Romney & D’Andrade, 1964). Rank or position on lists is a second measure because words mentioned first on lists would seem more salient than words mentioned at the end (Bousefield & Barclay, 1950; Hammel, 1984; Hammel & Yarbrough, 1974). The third measure, Smith’s S, takes into account both frequency and rank and is computed by dividing the sum of a word’s percentile ranks by the total number of lists (Smith, 1993). Table 2 displays the first 12 entries for both Anglo English and Mexican Spanish for young and older groups ordered by Smith’s S. Generally words with the highest frequency also have the highest rank, but not always. The trade-off can be seen in the young Mexicans’ list where amor (love) is less frequent (appearing

29

24

17

15

13

13

13

13

8

7

11

Sad

Angry

Excited

Afraid

Love

Depressed

Anxious

Confused

Frustrated

Ecstatic

Exhausted

22

22

18

15

Sad

Happy

Angry

Love

Freq

29

Happy

Older Anglos

Freq

Young Anglos

3.07

4.11

4.27

4.00

Rank

8.73

6.29

5.88

7.77

6.31

5.54

4.92

6.00

4.41

5.25

3.07

1.86

Rank

0.39

0.42

0.52

0.53

Smith

0.13

0.13

0.14

0.18

0.19

0.22

0.27

0.29

0.36

0.47

0.78

0.87

Smith

3.00

1.00

3.00

1.00

Val

1.00

3.00

1.00

2.00

2.00

1.00

3.00

1.00

3.00

1.00

1.00

3.00

Val

Amor

Coraje

Tristeza

Alegrıá

Older Mexicans

Nostalgia

Dolor

Pasion

Miedo

Rencor

Depresion

Carinõ

Coraje

Odio

Tristeza

Alegria

Amor

Young Mexicans

12

19

20

27

Freq

7

5

9

10

9

11

14

18

19

22

26

25

Freq

Table 2 12 emotion words with highest psychocultural salience: young and old, Anglo and Mexican groups

3.00

4.74

3.30

2.93

Rank

6.00

4.80

7.44

5.60

5.33

5.82

6.79

5.89

3.84

3.59

3.96

3.36

Rank

0.31

0.33

0.51

0.73

Smith

0.12

0.12

0.15

0.16

0.18

0.19

0.21

0.31

0.43

0.53

0.60

0.64

Smith

3.00

1.00

1.00

3.00

Val

2.00

1.00

3.00

1.00

1.00

1.00

3.00

1.00

1.00

1.00

3.00

3.00

Val

The Preponderance of Negative Emotion Words in the Emotion Lexicon 275

11

12

11

14

8

9

8

5

Hurt

Funny

Afraid

Depressed

Exhausted

Excited

Anxious

Freq

Hate

Young Anglos

Table 2 (Continued )

3.40

7.25

7.22

3.88

7.79

5.64

5.75

3.91

Rank

0.12

0.13

0.15

0.19

0.19

0.22

0.24

0.25

Smith

1.00

3.00

1.00

1.00

1.00

3.00

1.00

1.00

Val

Rencor

Angustia

Carinõ

Odio

Depresion

Miedo

Dolor

Nostalgia

Young Mexicans Mexicans Older

5

5

7

7

8

5

7

8

Freq

5.00

4.20

4.86

5.43

5.88

3.40

4.43

3.00

Rank

0.10

0.11

0.12

0.12

0.13

0.14

0.14

0.18

Smith

1.00

1.00

3.00

1.00

1.00

1.00

1.00

2.00

Val

276



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on 25 lists) than alegrıá (happiness; appearing on 26 lists) but has a higher Smith’s S score and hence is more salient. Valence Hypothesis 1 predicts higher numbers of negative emotion labels relative to positive labels in general. Hypothesis 3 predicts that young and older people will not differ in having proportionally more negative than positive emotion terms in their vocabularies. Both of these predictions are tested via a 2 /3 repeated measures ANOVA with age group (young versus old */collapsing across cultures) as the between-groups variable and valence as the withinsubjects variable (positive, neutral and negative). The dependent measure in this case is numbers of positive, neutral and negative terms. Results show no main effect of young versus old age groups (Ms /3.28 versus 3.06), F (1,119) /0.96, but a main effect of valence, F (2,238)/90.04, p B/0.001, and no interaction. Post-hoc tests indicate that the number of negative emotion labels (M /4.77) was significantly higher than numbers of either neutral (M /1.63, F /137.66, p B/0.001) or positive (M /3.12; F /57.82, p B/0.001) emotion labels. In sum, negatively valenced terms outnumbered neutral and positive terms, and younger people did not differ from older people in this regard. A similar 2 (age group)/2 (valence) ANOVA using proportions of negative, positive and neutral emotions labels as the dependent variable showed no differences between age groups. Figure 1 shows that about 50% of all terms are negative, 30% are positive and 20% are neutral, and that there is little difference between groups. The composition of emotion lexicons Hypothesis 2 predicts that older individuals will have more diverse emotion lexicons than younger individuals. Testing this hypothesis requires determining how many unique emotion labels were produced by each group and then measuring their frequency across individuals to devise some

Figure 1 Pie charts showing the proportions of emotion labels in younger and older groups.

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measure of idiosyncrasy that will serve to characterise the diversity of each person’s lexicon. These analyses will be done for the four groups: Young Anglos, Older Anglos, Young Mexicans and Older Mexicans. While groups produced about 300 words each, they differed in the number of distinct emotion labels per group, with older groups producing more numerous distinct labels than younger groups. Young Anglos recalled 301 words but, with repeats, only 52 distinct emotion labels. Older Anglos recalled 295 words as a group, but, with repeats, 81 distinct emotion labels. This same age difference is apparent for the Mexicans, where young Mexicans recalled 300 words but 63 distinct labels, and where older Mexicans recalled 298 words and 79 distinct labels. Thus, the younger groups call on a smaller network, and older individuals call on a larger network of emotion labels in their free recalls. This difference was further probed by counting the number of labels shared across age groups. Among Anglos, young and old groups mention in common 31 distinct emotion labels. Since the young group produced 52 labels in total, this means that they mentioned an additional 21 (idiosyncratic) emotions not mentioned by the older Anglo group. The older group mentioned 50 idiosyncratic terms not mentioned by the young group. Figure 2 displays these differences in pie charts by plotting the proportions of shared terms between young and old in black and the proportions of terms unique to each age group (and hence unshared with the other group) in grey. The increase in numbers of unshared or idiosyncratic terms in the older groups can be seen by comparing grey areas across age groups. Thus, discounting the pool of emotion labels shared by young and old groups, and counting the idiosyncratic labels, we can see that older groups do not simply start with the same labels as young people and add terms. Rather both groups mention labels not mentioned by the other group, but older groups mention more such terms. To test for the statistical significance of these differences, an ‘idiosyncrasy score’ was computed for each individual by assigning to each word in each list the group-level frequency score for that word and then computing an average of these frequencies for each list. Thus, for example, if an individual in the young Anglo group listed the words ‘happy’, ‘angry’, ‘love’ and ‘frustrated’, we would assign group frequencies (according to Table 2) as follows: ‘happy’ (29), ‘angry’ (24), ‘love’ (13) and ‘frustrated’ (8). The average of these comprises the idiosyncrasy score (18.5). Since the less frequent a word, the lower its (group) frequency score, the participant who has many infrequent words will have a lower score than the participant who mentions only very high frequency words. A lower score therefore indicates that a participant’s list contains more numerous infrequent words. Results showed that older members in both cultural groups shared fewer words among themselves than young people shared among themselves. Older Anglos had lower scores (M /9.93, sd /2.55) than young Anglos (M /14.33, sd/2.72). Older Mexicans had lower scores (M /9.96, sd /3.57) than did young Mexicans (M /12.66, sd /2.43). A 2 (Anglos versus Mexicans)/2 (young versus older) ANOVA resulted in no significant effect of cultural group (F(1,117) /2.51, MSE /20.34), a main effect of age group (F (1,117) /47.10, MSE /382.11, p B/0.001) and no interaction (F (1,117) /2.67, MSE /21.72). In conclusion, among themselves older individuals show a greater variability

The Preponderance of Negative Emotion Words in the Emotion Lexicon Young Anglos

Terms shared with Older Anglos: 0.60 Terms unique to Young Anglos: 0.40

Young Mexicans


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Older Anglos

Terms shared with Young Anglos: 0.40 Terms unique to Older Anglos: 0.60

Older Mexicans


Figure 2 Pie charts showing the proportions of emotion labels shared by young and old groups (in black) and proportion of labels unique to each group (grey). Larger grey areas in older versus young charts show larger proportions of unique or idiosyncratic terms unshared with the younger participants.

in their recalls than do younger participants. That is, older individuals mention fewer shared words among themselves than do young people. Valence and language Hypothesis 4 predicts that the relative proportions of negative, neutral and positive labels (approximately 50%, 20% and 30% respectively) will not differ between language groups. A 2 /3 repeated measures ANOVA with culture (Anglo versus Mexican) as the between-subjects variable and valence (positive, neutral, negative) as the within-subjects variable showed no main effect of culture (F (1,119) /1.45, n.s.), a main effect of valence (F(2,238) /90.32, p B/0.001) and no interaction. The main effect of valence repeated the results found above. Negative emotion labels were significantly more numerous than neutral emotion labels (F /136.89) and significantly more numerous than positive labels (F /59.77). Conducting the ANOVA on proportions of negative, neutral and positive terms produced the same

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results: no main effect of culture group, a main effect of valence (Anglos: 51%, 19%, 30%; Mexicans: 48%, 16%, 36%) and no interaction. Overall, the hypotheses of this paper were supported. Hypothesis 1 predicted that more negative versus positive emotion labels would be found in the working emotion vocabulary. Negative emotion labels made up approximately 50% of free-listed emotions, while positive labels accounted for approximately 30% and neutral labels for 20%. Hypothesis 2 predicted that older adults would have more diverse emotion lexicons than younger adults. By assigning to each emotion term mentioned by each individual the frequency score for that term in the group as a whole, we computed an idiosyncrasy score for each person. Persons with lower average idiosyncrasy scores shared fewer terms with others of his or her group. Older individuals scored significantly lower than younger persons, indicating more diverse vocabularies. As Hypothesis 3 predicted, however, older participants’ more diverse lexicons preserved the proportional balance of negative, neutral and positive labels seen before. Finally, we looked for cross-linguistic variation in the preponderance of negative emotion labels (Hypothesis 4) but found no differences between monolingual Spanish speakers and monolingual English speakers. Again, negative labels significantly outnumbered neutral and positive labels.

Discussion Negative emotion labels predominate over positive and neutral terms in the working emotion vocabulary of the average individual. We suggest that this is not a statement about emotional experience. That is, it does not imply that humans have more negative than positive emotional experience. Rather it seems to be a statement about human cognition. The theories we have reviewed about the cognitive processing of emotional experience argue that negative and positive emotions are subjected to different kinds of processing. These theories assert that we tend to take positive emotions as signals that the environment is benign and safe, and we interpret our experience of that environment by fitting it into the mental schemata we have already acquired about the world and ourselves. Such schema-driven processing is efficient and easy and perhaps ‘comfortable’. Negative emotions, on the other hand, signal that the environment is problematic or threatening in some way, and we tend to interpret that environment by analysing it in a more detailed fashion. Such systematic processing is more effortful and perhaps ‘careful’. One of the many functions of words is referential, and as phenomena become more complex, more names will be employed to interpret and analyse them. In this sense, the more detailed cognitive processing triggered by negative emotions also results in more negative than positive emotion labels. These proportions of negative to positive emotion labels are roughly the same in younger and older samples. On the one hand, research on mechanisms of emotion regulation shows that young people have less of a tendency to emphasise the positive and to dampen negative affect than do older people (affect-optimisation). A lower emphasis on positive emotion compounded by heuristic processing predicts low lexification of positive


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emotion. Young people also have less facility in coordinating and managing complex emotional experience than do older people (affect-complexity), but as they engage in the developmental task of affect-complexity their detailed processing of negative experience versus heuristic processing of positive experience generates greater lexification of negative emotion terms. For young people, then, negative emotion labels predominate over positive emotion labels. On the other hand, for older people, although there is an increase in affect-optimisation, the tendency to emphasise positive emotion is again accompanied by continued schematic processing and predicts fewer positive than negative emotion terms. Contrariwise, growth in affect-complexity is accompanied by continued systematic processing and predicts more negative emotion terms. Again, this is what we see. In the end, the proportions of negative and positive terms remain the same. Although our data concern only two cultures and languages, it is possible that these observations would hold cross-culturally. In this study we found no differences in the relative proportions of negative, neutral and positive terms between the urban Mexican and urban US groups that we examined. These results converge with the literature on basic emotions. That research suggests that there is a limited set of underlying emotional experiences that are pancultural but that these may not have exact translation equivalents across languages. For example, using questionnaires in 37 countries on five continents, Scherer and Wallbott (1994) found highly similar patterning of feeling, physiological symptoms and expression across cultures for seven emotion experiences, glossed in English as ‘joy’, ‘anger’, ‘fear’, ‘sadness’, ‘disgust’, ‘shame’ and ‘guilt’. Similarly, but in an explicitly lexical study, Frijda and associates (1995) reviewed data from 11 cultural groups and pointed out that the following emotions were mentioned by at least 20% of the respondents in the groups reviewed (again glossed in English): ‘joy’ or ‘happiness’ (10 of 11), ‘sadness’ (all 11), ‘anger’ (all 11) and ‘fear’ (10 of 11). Equivalents of the English ‘hate’ were mentioned in 6 of 11 groups. Whether and to what extent basic emotions are present and lexified in any culture should probably remain an empirical issue as the danger always exists of imposing the categories of one’s own culture. Nevertheless, it is instructive to note that in both these lists, negative terms predominate. In Scherer and Wallbott’s list of seven labels, only one is positive (joy), and in the Frijda et al .’s list of five emotions, again only one label is positive (joy or happiness). While further empirical work would be necessary to confirm that negative labels predominate in the working vocabularies of individuals cross-culturally, these results suggest that it is a likely hypothesis. The influence of culture on the cognition of emotion goes well beyond the theories and predictions made in this study, and it is important to point out some of these as a way of framing our contributions and indicating its limitations. According to the cognitive model of emotion (for review, see Mesquita & Frijda, 1992), of which the theories of this paper serve as a subset, the emotional response to environmental stimuli involves several crucial cognitive components, each intimately shaped by culture. A first observation is that the environmental stimuli, or the antecedent events, that activate emotional response are themselves different in different cultural

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surroundings. Thus, for example, rural versus urban environments, hierarchical versus egalitarian social structure, situations of civil war or peace, all present different types of regularly occurring events that activate affective responses. Secondly, in response, individuals code or categorise such events as particular kinds of events with expectable implications and outcomes, and this coding is also pervasively shaped by the culture to which one belongs. Finally, individuals make appraisals of these events. That is, individuals evaluate how their lives and well-being will be affected by the events. Each of these key moments in the cognitive appraisal of emotion situations opens a window onto the cross-cultural variation in emotion processing (Scherer, 1997, 1999). In terms of the interests that motivate the research that we have reported here, each of these moments offers a potential site for understanding the lexification of emotion. As an initial approach, we have focused on the working emotion vocabulary in isolation from explicitly emotional experience, but the framework within which we work offers additional and promising avenues of research on the complex interplay of emotion, cognition and language.

Conclusion In one sense the empirical finding of this paper is fairly simple: negative emotion labels predominate over positive labels in the working emotion vocabulary, both cross-generationally and cross-culturally (in the Mexican Spanish and US English samples that we examined). Nevertheless, because these results are consistent with the theories that predict them, they make an important point about how cognition constrains the lexification of emotion. Negative emotion labels predominate because the cognitive processing triggered by negative emotions is more detailed and systematic than the cognitive processing triggered by positive emotions, and this more detailed processing results in more emotion labels. This implies a common cognitive constraint on each of the languages that multilingual and multicultural individuals speak. Although in this study we sampled only English and Spanish speakers, we predict that future studies of other languages will find the same effect. Acknowledgement This research was supported by the National Institute on Aging grant AG16340. Correspondence Any correspondence should be directed to Dr Robert W. Schrauf, Buehler Center on Aging, Northwestern University, 750 North Lake Shore Drive, Suite 601, Chicago, IL 60611-2611, USA ([email protected]). References Altarriba, J. and Bauer, L.M. (2004) The distinctiveness of emotion concepts: A comparison between emotion, abstract, and concrete words. American Journal of Psychology.


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Bless, H., Clore, G.L., Staudinger, N., Golisano, V., Rabe, C. and Wolk, M. (1999) Mood and the use of scripts: Does a happy mood really lead to mindlessness? Journal of Personality and Social Psychology 71, 665 /679. Borgatti, S. (1996) Anthropac 4.983 . Natick, MA: Analytic Technologies. Boucher, J.D. (1979) Culture and emotion. In A.J. Marsella, R.G. Tharp and T.V. Ciborowski (eds) Perspectives on Cross-cultural Psychology (pp. 159 /178). San Diego, CA: Academic Press. Bousefield, W. and Barclay, W. (1950) The relationship between order and frequency of occurrence of restricted associative responses. Journal of Experimental Psychology 40, 643/647. Brewer, D. (1995) Cognitive indicators of knowledge in semantic domains. Journal of Quantitative Anthropology 5, 107/128. Cacioppo, J.T., Gardner, W.I. and Berntson, G.G. (1998) The affect system: Form follows function. Journal of Personality and Social Psychology 76 (5), 839/855. Cacioppo, J.T. and Gardner, W.L. (1999) Emotion. Annual Review of Psychology 50, 191/ 214. Carstensen, L.L. (1995) Evidence of a lifespan theory of socioemotional selectivity. Current Directions in Psychological Science 4, 151/156. Church, A.T., Katigbak, M.S. and Reyes, J.A.S. (1996) Toward a taxonomy of trait adjectives in Filipino: Comparing personality lexicons across cultures. European Journal of Personality 10, 3 /24. Church, T.A., Katigbak, M.S., Reyes, J.A.S. and Jensen, S.M. (1998) Language and organization of Filipino emotion concepts: Comparing emotion concepts and dimensions across cultures. Cognition and Emotion 12 (1), 63 /92. Clore, G.L., Ortony, A. and Foss, M.A. (1987) The psychological foundations of the affective lexicon. Journal of Personality and Social Psychology 53, 751/766. Diener, E., Colvin, C.R., Pavot, W.G. and Allman, A. (1991) The cost of intense positive emotions. Journal of Personality and Social Psychology 61, 492/503. Frijda, N.H., Markam, S., Sato, K. and Wiers, R. (1995) Emotion and emotion words. In J.A. Russell, J.M. Fernandez-Dols, A.S.R. Manstead and J.C. Wellenkamp (eds) Everyday Conceptions of Emotion (pp. 121 /143). Dordrecht, Netherlands: Kluwer. Gatewood, J. (1984) Familiarity, vocabulary size, and recognition ability in four semantic domains. American Ethnologist 11, 507/527. Hammel, E. (1984) Cognitive order in genealogical lists. Journal of Anthropological Research 40, 60 /77. Hammel, E. and Yarbrough, C. (1974) Preference and recall in Serbian courtship: Power and kinship ideology. Journal of Anthropological Research 30, 95 /115. Hoekstra, H.A. (1986) Cognition and Affect in the Appraisal of Events . Groningen, The Netherlands: Rijksuniversiteit Groningen. Izard, C.E. (1993) Four systems for emotion activation: Cognitive and noncognitive processes. Psychological Review 100 (1), 68 /90. Labouvie-Vief, G. and Medler, M. (2002) Affect optimization and affect-complexity: Modes and styles of regulation in adulthood. Psychology and Aging 17 (4), 571/588. Mesquita, B. and Frijda, N.H. (1992) Cultural variations in emotions: A review. Psychological Bulletin 112 (2), 179 /204. Romney, A.K. and D’Andrade, R. (1964) Cognitive aspects of English kin terms. American Anthropologist 66 (3), Part 2, 146 /170. Romney, A.K., Weller, S.C. and Batchelder, W.H. (1986) Culture as consensus: A theory of culture and informant accuracy. American Anthropologist 88 (2), 313 /338. Russell, J.A. (1991) Culture and the categorization of emotions. Psychological Bulletin 110 (3), 426 /450. Scherer, K.R. (1997) Profiles of emotion-antecedent appraisal: Testing theoretical predictions across cultures. Cognition and Emotion 11 (2), 113 /150. Scherer, K.R. (1999) Appraisal theory. In T. Dalgleish and M.J. Power (eds) Handbook of Cognition and Emotion (pp. 637/663). New York: John Wiley.

284


Scherer, K.R. and Wallbott, H.G. (1994) Evidence for universality and cultural variation of differential emotion response patterning. Journal of Personality and Social Psychology 66 (2), 310 /328. Schwarz, N. (1990) Feelings as information: Informational and motivational functions of affective states. In R.M. Sorrentino and E.T. Higgins (eds) Handbook of Motivation and Cognition: Foundations of Social Behavior (Vol.2) (pp. 527/561). New York: Guilford Press. Schwarz, N. and Bless, H. (1991) Happy and mindless, but sad and smart? The impact of affective states on analytic reasoning. In J. Forgas (ed.) Emotion and Social Judgments (pp. 55 /71). Oxford: Pergamon Press. Schwarz, N. and Clore, G.L. (1983) Mood, misattribution, and judgements of wellbeing: Informative and directive functions of affective states. Journal of Personality and Social Psychology 45, 513 /523. Smith, J.J. (1993) Using ANTHROPAC 3.5 and a spreadsheet to compute a free-list salience index. Cultural Anthropology Methods 5 (3), 1/3. Staudinger, U.M., Marsiske, M. and Baltes, P.B. (1995) Resilience and reserve capacity in later adulthood: Potentials and limits of development across the lifespan. In D. Chicchetti and J. Cohen (eds) Developmental Psychopathology: Risk, Disorder, and Adaptation (Vol.23) (pp. 801/847). New York: Wiley. Storm, C. and Storm, T. (1987) A taxonomic study of the vocabulary of emotions. Journal of Personality and Social Psychology 53, 805 /816. Wallace, A.F.C. and Carson, M.T. (1973) Sharing and diversity in emotion terminology. Ethos 1, 1/29. Watson, D. and Clark, L.A. (1992) Affects separable and inseparable: On the hierarchical arrangement of the negative affects. Journal of Personality and Social Psychology 62, 489 /505. Zautra, A.J., Potter, P.T. and Reich, J.W. (1997) The independence of affects is contextdependent: An integrative model of the relationship between positive and negative affect. Annual Review of Gerontology and Geriatrics 17, 75 /103.

Appendix Free-listing instructions given in English The next category is emotions. This time, I’m asking you to list as many different emotions as you can (both good and bad). Once you are finished with the list, go back and check each item to see if it makes you think of anything else. Please indicate whether you consider each emotion as: unpleasant, neutral, or pleasant. Free-listing instructions in Spanish La siguiente categoria es tipo de emociones/sentimientos. Ahora quiero que haga una lista de emociones, (ya sean buenas o malas; positivas o negativas). Cuando termine, revise la lista a ver si le recordan otras emociones. Indique, si considera que esta emocioń es: desagradable, neutral, o agradable.