a reconsideration of the structure of the emotion …nalvarado/pdfs/areconsideration.pdf · a...

Motivation and Emotion, Vol. 22, No. 4,1998

A Reconsideration of the Structureof the Emotion Lexicon1

Nancy Alvarado2

University of California, Irvine

This study replicated a pile sort task involving 135 emotion terms originally pre-sented by Shaver, Schwartz, Kirson, and O'Connor (1987) with a slight change inprocedures, from an unconstrained single-sort task to a constrained successive-sort task, made necessary by methodological problems during their data analysis.Subjects (86 male and female undergraduates) were asked to assign names to theirpiles during the successive stages of sorting. This change produced a hierarchi-cal cluster analysis solution supporting interpretations other than the prototypestructure found by Shaver et al.. Decision criteria reported by subjects duringsorting were described and revealed dimensions reported by previous investiga-tors, suggesting that this is a viable method of determining dimensions importantin distinguishing emotion terms.

Shaver, Schwartz, Kirson, and O'Connor (1987) proposed a structure based onprototype theory to describe the hierarchical cluster analysis of sorting of 135emotion terms drawn from the emotion lexicon. Shaver et al. reported a solutionconsisting of six "fuzzy" categories, each containing both general and specificterms belonging to a single emotion family, and each characterized by a single basiclevel term: love, joy, surprise, anger, sadness, fear. However, their methodology wasflawed due to the aggregation of data produced using a single unconstrained sort,causing data from subjects sorting into fewer piles to be weighted more heavily

1Preparation of this article was supported in part by National Institute of Mental Health grant MH18931to Paul Ekman and Robert Levenson for the NIMH Postdoctoral Training Program in Emotion Re-search. Portions of this work were completed as part of a doctoral dissertation (see Alvarado, 1993).

I gratefully acknowledge the assistance of Louis Narens, Paul Ekman and William Irwin in thecompletion of this work. I also thank the UC Irvine Semiotics Laboratory research assistants for theirhelp with data collection.

2Nancy Alvarado is now at the Center for Human Information Processing, University of California atSan Diego, 9300 Gilman Dr., MC-0109, La Jolla, California 92093-0109.

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0146-7239/98/1200-0329$15.00 © 1998 Plenum Publishing Corporation

than data from subjects sorting into more piles. A replication correcting this flaw,presented here, suggests a different solution and interpretation.

The study reported here performed successive constrained sorts rather thana single unconstrained sort. It kept most other procedures identical to the Shaveret al. (1987) study. An additional procedure was added in order to collect additionalinformation about the basis for subject decisions. Subjects were asked to label theirpiles at each stage of the successive sort. If the underlying structure proposed byShaver et al. were present in the lexicon, it was expected that the results wouldconfirm those of Shaver et al.. However, it will be shown that a small proceduralchange has a large impact upon the clustering solution, calling into question theclaims for prototypicality of certain emotion terms made by Shaver et al.

METHOD

The pile sort task reported by Shaver et al. (1987) was replicated with confor-mance in every respect except the location (University of California), numberof subjects (86 vs. 100 male and female undergraduates), and the use of a suc-cessive, constrained sort procedure rather than a single, unconstrained sort, asdescribed below. Modifications to the sort procedure for the present study weremade because, according to Weller and Romney (1988), data from individual, sin-gle unconstrained sorts may not be aggregated, and because a successive sort betterallows a hierarchical structure to emerge during cluster analysis. Addition of thenaming procedure allows evaluation of whether the taxonomic structure imposedby successive sorting is appropriate to the domain.

Materials

Each of the 135 emotion terms used by Shaver et al. (1987) was printed on a2-in. x 4-in. card. Cards were shuffled before each session. See Shaver et al. for adescription of the method used to define the domain of emotion terms and verifythe suitability of items as members of that domain.

Procedure

Subjects were asked to sort the 135 cards into two piles based on meaning.After sorting the terms into two piles, the subject was asked to assign a nameto each of the piles. These two steps were repeated until each of the first twopiles was subdivided into two piles, and each of those was again subdivided intotwo piles. This resulted in a three-level sorting hierarchy with two piles at thefirst level, four at the second, and eight at the third level. Sorting stopped afterthree levels because sorting 135 items into additional levels would have presented

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practical difficulties for both subjects and experimenter. All subjects sorted intothe same number of piles. The assignment of names to each sorted pile was madein order to investigate the rule or criteria subjects were using at each point in theprocess.

RESULTS

Cluster Analysis

Hierarchical cluster analysis was conducted as closely as possible to theway in which it was performed by Shaver et al. (1987). Individual 135 x 135co-occurrence matrixes (hereafter called proximity matrixes) were constructedby computing the percentages of co-occurrences between items across the 14piles for each subject. The individual matrixes were combined by computing themean percentages of co-occurrences between items rather than by aggregatingfrequencies. These differences in computing the aggregate proximity matrix werenecessary both to adjust for the difference in number of subjects and in order toweight each subject's responses equally. Constraining the number of piles permitsthis.3

In the method of aggregating data used by Shaver et al., responses of sub-jects with fewer piles were inadvertently weighted more heavily than responsesof subjects with more piles. How this occurs is demonstrated in Fig. 1. If twosubjects each sort 10 items into any number of piles, and Subject 1 sorts as shownin Fig. la, while Subject 2 sorts as shown in Fig. 1b, it can be seen that manymore columns are incremented in the proximity matrix for Subject 2 than forSubject 1 (ignoring the diagonals). This is not a problem unless the data are ag-gregated. When the data in Figs, 1a and 1b are added together, it can be seen thatSubject 2 contributed more heavily to the combined matrix than Subject 1, withthe net effect of weighting Subject 2's responses in the resulting cluster analysissolution.

The aggregate proximity matrix was analyzed using Johnson's hierarchicalclustering algorithm, as implemented by Borgatti (1993) in Anthropac Version4.02. This algorithm is essentially the same as that implemented in BMDP 1M,as used by Shaver et al. (1987). The average distance method was used, as in theprevious study. Results are shown in Fig. 2 and Table I.

Compared to the cluster solution produced by Shaver et al. (1987) (repro-duced here as Fig. 3 and Table I), a more differentiated hierarchical structure was

3 Boster has developed an alternative technique for circumventing this problem that allows subjectsto sort into as many piles as desired, but also provides consistent input data (see Weller & Romney,1988). However, this technique is only workable with a much smaller set of items due to the burdenit places upon subjects.

331Determining the Structure of the Emotion Lexicon

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Fig. 1. Comparison of proximity matrices for two sorting strategies.

produced, as would be expected from the change in sort procedure. While thereare obvious similarities between the two solutions, the number of negative pilesis greater in this solution, and the kinds of terms contributing to those piles aredifferent. A few terms have switched from being negative to positive and vice versa(i.e., longing, sympathy).

Even without any analysis of prototypicality, it appears obvious that the tran-sition from general through basic (at 50) to specific in the subcategories describedby Shaver et al. (1987) is not evident in this solution. Without this organizingprinciple, it makes no sense to name the nodes using basic emotion terms (e.g.,lust and melancholy are unlikely candidates for basic terms). Selection of 50 asa "basic level" by Shaver et al. was arbitrary. Note that in Fig. 2, use of 50 as acutoff selects a very different set of categories than in Fig. 3, due to the deeperhierarchical structure of the solution in Fig. 2.

Analysis of Centrality

The terms produced by this analysis can be subjected to the same type of pro-totypicality analysis used by Shaver et al. (1987) through comparison of centralityscores, but given the composition of the categories, the resulting basic level termsare likely to be unsatisfactory in the context of prototype theory. Multidimensionalscaling (MDS) also provides a visual display of the analysis of centrality per-formed by Shaver et al.. The most basic or central items within a category willalso tend to be those nearest the origin in an MDS plot of the data upon whichcentrality was calculated (Weller & Romney, 1988). This analysis used MINISSA,as implemented by Borgatti (1993) in Anthropac, Version 4.02.

To test, using data from this study, Shaver et al.'s (1987) claim that love is abasic term, different combinations of subgroups of positive terms, all taken fromFig. 2 and Table I at different levels of division, were scaled. Love was the mostcentral term only when the categories with passion terms were scaled togetherwith those representing affection and caring, and those relating to happiness, ex-citement, and joy were excluded. When the category containing love was scaled

Fig. 1—Continued

Determining the Structure of the Emotion Lexicon 333

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alone, affection was the central term. Because love is not central when the othersubcategories (happiness, excitement) are included, it makes no sense to label thehigher-level node love in Fig. 2, as was done in Fig. 3.

Without some justification for selecting one level of splitting or some combi-nation of clusters in preference to another, there is little way to determine whetherlove is a most prototypical term. It cannot be selected in preference to other choicesrevealed by analysis solely because the experimenter wishes it to be basic. Thatdilemma was also found by Shaver et al. (1987), where affection was found to bemost prototypical within a category but love was asserted in preference to it, onthe basis of theory.

Analysis of Pile Names

An inductive categorization of the kinds of names assigned by subjects to theirpiles yielded the sorting criteria listed in Table II. Guidelines for classification werebased upon the types of names given by subjects, as described below, and a count ofthe frequency of use of the various criteria was made for names assigned at each ofthe three sorting levels. These classifications were made by two experimenters, withdisputes resolved by discussion.4 Results of this tabulation are shown in Table II.

The categories listed in Table II are defined as follows (the/symbol separatesthe two category names and examples of subject responses are enclosed in

4I thank William B. Irwin for his help with this portion of the analysis.

Fig. 3. Results of cluster analysis for unconstrained single sort of 135 emotion terms. (From "EmotionKnowledge: Further Exploration of a Prototype Approach" by P. Shaver, J. Schwartz, D. Kirson, andC. O'Connor, 1987, Journal of Personality and Social Psychology, 52, pp. 1061-1086. Copyright1987 by the American Psychological Association. Reprinted by permission.)

336 Alvarado

Table I. List of Items Clustered in Categories Shown in Figs. 2 and 3

Category Numbera

1

2

3

4

5

Figure 2 Items

pleasuresatisfaction

reliefoptimismhopeeagerness

joypridecontentmentgaietygleedelightjollinessjovialitygladnesscheerfulnesshappinessamusementenjoyment

adorationlovecaringtendernessaffectionfondnesscompassionlikingsentimentalityblisssympathyrapture

passionecstasyarousaldesireattraction

Figure 3 Items

adorationaffectionlovefondnesslikingattractioncaringtendernesscompassionsentimentality

arousaldesirelustpassioninfatuation

longing

amusementblisscheerfulnessgaietygleejollinessjovialityjoydelightenjoymentgladnesshappinessjubilationelationsatisfactionecstasyeuphoria

enthusiasmzealzestexcitementthrillexhilaration

(Continued)


Table I-Continued

Category Numbera

6

7

8

9

10

11

12

13

14

Figure 2 Items

euphoriaenthrallment

zestzealastonishment

jubilationexcitementexhilarationelation

enthusiasmamazementthrilltriumphsurprise

lustinfatuation

melancholylonging

loathingspitehatehostilityscorn

wrathangerragefuryoutrageferocityvengefulnesscontempt

insultdisgustrevulsion

Figure 3 Items

contentmentpleasure

pridetriumph

eagernesshopeoptimism

enthrallmentrapture

relief

amazementsurpriseastonishment

aggravationirritationagitationannoyancegrouchinessgrumpiness

exasperationfrustration

angerrageoutragefurywrathhostilityferocitybitternesshateloathingscornspitevengefulnessdislikeresentment

(Continued)

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Table I— Continued

Category Numbera

15

16

17

18

19

20

21

22

Figure 2 Items

dreadfearfrightpanic

miserysufferinganguish

tormentterrorhorroragonyhysteriamortification

rejectionalienationdejectionisolation

defeathumiliationshame

pityregretguilt

embarrassmenttensenessinsecurityuneasinessworrynervousnessanxiety

woeremorsegriefdistress

Figure 3 Items

disgustrevulsioncontempt

envyjealousy

torment

agonysufferinghurtanguish

depressiondespairhopelessnessgloomglumnesssadnessunhappinessgriefsorrowwoemiserymelancholy

dismaydisappointmentdispleasure

guiltshameremorseregret

alienationisolationneglectlonelinessrejectionhomesicknessdefeatdejectioninsecurityembarrassmenthumiliationinsult

(Continued)


Table I— Continued

Category Numbera

23

24

25

26

27

28

29

30

Figure 2 Items

despairdepressionhopelessness

homesicknessgloomsorrowsadnesslonelinessunhappinessglumness

hurtdispleasuredismaydisappointmentneglect

exasperationalarmshockapprehension

frustrationgrouchinessgrumpiness

envyjealousy

bitternessresentment

dislikeaggravationannoyanceirritationagitation

Figure 3 Items

pitysympathy

alarmshockfearfrighthorrorterrorpanichysteriamortification

anxietynervousnesstensenessuneasinessapprehensionworrydistressdread

aCorresponds to numbers shown in Figs. 2 and 3.

quotation marks). Note that each category names two piles, because at each levelthe procedure required subjects to divide a single pile in two. Category 1 (positive/negative) corresponds to Osgood's (1966) concept of evaluation, and consists ofnames like good/bad, happy/sad, optimistic/pessimistic, and secure/insecure. Cat-egory 2 (intensity) corresponds to Osgood's concepts of activity and potency, andconsists of names like strong/weak and more/less. Category 3 (duration) was codedwhen subjects sorted on the basis of the length of experience of an emotion, andincluded names like emotions/moods. Category 4 (self vs. others as source or

Table II. Categorization Rules Used by Subjects During Pile Son

Criterion

1. Evaluation2. Intensity3. Duration4. Self/others5. Relationship6. Categorical7. General/specific8. Judgmental9. Show/feel

10. Definitional11. Controllability12. Undifferentiated13. Unclassifiable

Frequency (%)a

Level 1

85.52.40.00.60.63.00.01.20.01.20.01.24.2

Level 2

Pos

3.619.91.8

18.111.414.53.02.44.86.00.0

10.24.2

Neg

6.621.1

1.215.110.218.71.83.01.83.60.0

13.33.6

Level 3

Pos

3.012.02.4

18.19.0

24.72.40.04.84.20.6

12.76.0

Pos

2.413.91.8

13.910.830.1

1.20.63.03.60.0

13.94.8

Neg

1.219.30.6

13.314.527.72.40.06.01.80.69.63.0

Neg

1.218.70.6

11.48.4

28.91.21.24.21.21.8

15.75.4

a N = 84. Pos = positive; Neg = negative.

object) was coded whenever a subject made reference to the source or object ofemotion. It generally corresponded to DeRiviera and Grinkis's (1986) distinctionsamong emotions and encompassed names like internal/external or active/passiveas well as more explicit designations, e.g., things you feel about other people.Category 5 (relationship) was coded whenever the subject distinguished betweenlove and other relationships, between love and sex, or between emotions felt inrelationships versus all other emotions. This was distinguished from Category 4on the basis of explicit mention of love or sex, or mention of relationship.

Category 6 (categorical) corresponded most closely to the prototype theorysort criterion because the labels given might be considered to name "basic" emo-tions or exemplars. Names consisting of any single emotion term within the set of135 terms (not necessarily basic with respect to Shaver et al., 1987) were recordedas Category 6, e.g., fear/anger. Names consisting of single terms (not among the135 terms), e.g., bad feelings or pain, were coded as Category 12. Combiningthese two categories might yield a rough estimate of how many subjects sortedon the basis of resemblance to an exemplar emotion or prototype. Category 7 wascoded when the subject expressed an explicit concern for the specific versus gen-eral nature of the terms within the set, e.g., common/uncommon or everyday emo-tions/special occasion emotions. Category 8 was coded when subjects made strongexplicit reference to the judgmental quality (implicit references were coded as Cat-egory 1) e.g., what a good Christian feels/evil or abnormal/normal. In some senseall terms are evaluative and the distinction between Category 8 and Category 1 ismoot.

Category 9 (expression) was coded when subjects gave names distinguish-ing between emotions largely felt versus those readily expressed, e.g., show/feel.

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Category 10 (definitional) recorded subjects concerned with meta-aspects of thetask, e.g., personality traits versus states of being, distinguishing emotions fromfeelings, classifying nouns, adjectives and verbs, separating emotions from non-emotions. Category 11 (controllability) was implicitly related to strength ofemotion (Category 2), but was coded only when subjects explicitly mentionedcontrollability as a decision factor, e.g., out of control. As noted above, Cate-gory 12 was coded when subjects labeled the pile using a single, general emotionterm not encompassed within the sorted items, e.g., pain. Category 13 (unclassi-fiable) included idiosyncratic sort criteria, or mixed criteria not readily classifiedusing the structure described above. These ranged from aggression/victim, sym-pathetic/hostile, divorced/dysfunction to work and career/school or relationship,personal attacks/lonely words, animal-like/manufactured by society, or all nega-tive/emotions needed to live a full life.

Two names were generated at Level 1 and are described by a single sortcriterion in Table II. Four names were produced at Level 2, described by two sortcriteria, and eight names were produced at Level 3, described by four sort criteria.Where possible, the columns in Table II list criteria for positive items on the leftand negative on the right, if that criterion was applied at the first sort level. Thesame convention is used for the eight names produced at Level 3, with the left twocolumns positive and the right two columns negative, if applicable.

At first glance, it may appear from this tabulation that subjects used differentrules or criteria for dividing terms, in some cases very different. At the first level,although there was a strong preference for a negative/positive split (85.5%), 12subjects used some other basis for dividing the terms. Subjects were not necessarilyconsistent in applying their sort criteria, about 50% switching to different criteriaat different levels. Further, subjects frequently applied different criteria within alevel, i.e., sorting negative and positive piles differently. There appears to be aslight tendency to apply Category 2 (intensity) to negative terms and Category 4(self/other) to positive terms. (This result is confounded because not all subjectsmade the positive/negative split at Level 1.)

About 6% of subjects provided names at Level 2 that were inconsistent withtheir previous classification at Level 1 (e.g., sorting into good and bad at Level 1,then identifying a pile of "good" terms within a "bad" pile at Level 2). Suchintransitivities were rare (only one or two) at Level 3. Because they occurredprimarily within Category 1, they seem best characterized as a form of intensityjudgment for evaluation.

DISCUSSION

Two conclusions can be drawn from this solution: (1) this pile sort method-ology may be inappropriate for determining prototypicality of emotion termsand testing prototype theory; (2) dimensionality of the domain of emotion terms


found in previous studies appears to be dependent upon the type of judgmenttask presented to subjects. The differences between the previous solution and thisreplication clearly demonstrate the dependence of data reduction solutions on theprocedures used to collect data, the constituents of the input data matrixes, and thealgorithms used to analyze that data (in this case, the method of aggregating data).Little confirmation was found for Shaver et al.'s (1987) interpretation that emo-tion terms form families centered around prototypical terms. This approach doesdemonstrate a method of discovering choice dimensions implicit in lexical deci-sions, beyond those found using more traditional sorting and similarity judgmenttasks, as will be discussed more fully below.

Despite the methodological flaw, it is tempting to believe that the solutionfound by Shaver et al. (1987) must be correct because it intuitively "makes sense,"because it so clearly supports prototype theory, or because the alternative structurepresented here is less readily interpreted in the context of any theory. This wouldbe a mistake. No solution can be claimed as correct, no matter how attractive, whileit contains mathematical errors. It may be that a prototype structure does emergein the experimental circumstances provided by a single, unconstrained sort task.Reanalysis of Shaver et al. 's data with cluster analysis performed on an individual-by-individual basis is needed to confirm their result. The inadvertent overweightingof subjects with fewer piles is methodologically equivalent to including somesubjects multiple times within the same data set, while others are included onlyonce. To insist that the solution is nevertheless correct is equivalent to saying thatit is acceptable to include some subjects more often because the data come outbetter. This is especially so because the subjects overweighted are exactly thosesubjects most likely to produce the expected prototype-based solution.

The bias toward the responses of subjects with fewer piles may also be a biastoward a prototype structure because such a structure necessarily consists of fewpiles created using a single criterion (categorical resemblance to the most basicmember of that category, the prototype emotion). Psychophysical theory suggeststhat five to seven piles is an optimal number for sorting based upon discriminationof physical properties of objects, the kind of judgment that more typically resultsin emergence of prototypes. Sorting based upon more abstract, relational, or lessobservable features (like the criteria identified in Table II) is less compatible withprototype theory and may be more likely to result in finer sorting into a largernumber of piles.

There is no reason to believe that the sorting behavior of subjects in this studywas much different than the sorting behavior of subjects performing the single sortpresented by Shaver et al. (1987), although the possibility must be considered. Thewide range in the number of piles reported by Shaver et al. (2 to 65) suggests thatsubjects employed widely differing sort strategies, although all subjects may havebeen drawing upon the same cultural knowledge about the meanings of terms inthe emotion lexicon. The successive sort procedure with the naming of piles makes

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subject use of multiple sorting criteria highly visible, whereas it is more difficultto know what subjects were doing in the task presented by Shaver el al.

This study found a lexical structure that applies a different criterion at eachdescending node so that members of categories are distinguished by how theywere separated as each of these various criteria were applied. The analysis ofnaming data is important because it verifies that the taxonomic structure producedby the cluster analysis is appropriate to the domain (successive sorting can forceitems into an inappropriate taxonomic structure; Weller & Romney, 1988). In otherwords, the shift in criteria was found in the names provided by subjects and henceexists in their parsing of the domain of terms, rather than as an artifact of thecluster analysis algorithm. It is possible that the necessity to produce successivepiles produced the criteria. If so, this too is interesting because it demonstrates thata different methodology can produce information about different dimensions ofthe emotion lexicon. Theories of categorization have been assumed to be mutuallyexclusive. It may be that subjects are capable of using several cognitive processesfor categorization, that they switch between them as the situation demands, and thatthe characteristics of the task and the stimuli may determine which they employ(Nosofsky, 1986). There may also be personal preference among subjects for oneor another type of categorization process.

Sorting requires subjects to make similarity judgments about items. Whensubjects are constrained to two piles, they must decide whether items are the same ordifferent than previously sorted items. In contrast to a single sort task, a successivesort better allows subjects to shift dimensions as needed in order to optimize per-formance (Nosofsky, 1986). Unlike the single sort, subjects making successivesorts are forced to discover additional decision criteria, which may be trivial in theoverall implicit structure of the lexicon determined by multidimensional scaling ofall 135 terms, or by a single-sort procedure. In most studies, individual subjects whoprefer these additional criteria are seldom noted because scalings produced basedupon group data camouflage such diversity. Usually, the two major criteria notedin Table II emerge (Categories 1 and 2), with the remaining 10 considered noise.This procedure permits examination of the relative importance of decision criteria,as well as providing clues to a broader array of criteria (or dimensions for choice).

The solution produced by this study is less readily interpretable because itcombines data produced by subjects using widely different sorting strategies. Anycoherence likely results from the preferences for Category 1 at Level 1, followedby Category 2 at Level 2. Subjects must be constrained to the same sort criteriain order to produce a coherent solution with respect to the remaining dimensions.Even so, some support exists for other parsings of the emotion lexicon.

In contrast to Shaver et al.'s (1987) solution, this study (Fig. 2 and Table I)shows the internal/external distinction posited by Clore, Ortony, and Foss (1987)at the subordinate level (see also Ortony, Clore, and Foss, 1987). Clear subcate-gories for other-directed versus self-directed or other-inspired versus self-inspired


emotions exist (as suggested by DeRiviera and Grinkis, 1986). Clore et al.'s men-tal versus nonmental division appears in the separation of lust and infatuationfrom other forms of happiness, and in the distinction between passion and affec-tion. Clore et al.'s cognition, behavioral, and affect focal subcategories were allreflected in the decision criteria of certain subjects (see Table II). Further, severalsubjects made either an explicit or an implicit distinction on the basis of wordform (causative vs. noncausative), as discussed by Clore et al. (see especiallypp. 754,756, and 761 of their article). No evidence of the subjective versus objec-tive distinction in external conditions was found.

Conclusions

This work demonstrates that low-cost modifications to procedures can ensuregreater insight into the nature of a data reduction solution. The cluster analysisreported here sheds light on the dimensionality of similarity judgments based onthe emotion lexicon. As Nosofsky (1986) suggested, the salience of a dimensionfor subjects can be manipulated by the demands of a task and the characteristicsof stimulus items, producing different results in different experimental contexts,accounting for the divergence among results of the two studies described here.Whether a prototype structure applies to the emotion lexicon has yet to be demon-strated, but cannot be asserted on the basis of the analysis presented by Shaveret al. (1987).

REFERENCES

Aldenderfer, M, & Blushfleld, R. (1984). Cluster analysis. Beverly Hills, CA: Sage.Alvarado, N. (1993). The labeling of emotion. Unpublished doctoral dissertation, University of

California, Irvine. (University Microfilms International No. 9323902)Borgatti, S. (1993). Anthropac: Version 4.02. Columbia, SC: Analytic Technologies.Clore G., Ortony, A., & Foss, M. (1987). The psychological foundations of the affective lexicon.

Journal of Personality and Social Psychology, 53,751-766.DeRivera, J., & Grinkis, C. (1986). Emotions as social relationships. Motivation and Emotion, JO,

351-369.Nosofsky, R. (1986). Attention, similarity, and the identification-categorization relationship. Journal

of Experimental Psychology: General, 115,39-57.Ortony, A., Clore, G., & Foss, M. (1987). The referential structure of the affective lexicon. Cognitive

Science, 11,361-384.Osgood, C. (1966). Dimensionality of the semantic space for communication via facial expressions.

Scandinavian Journal of Psychology, 7,1-30.Shaver, P., Schwartz, J., Kirson, D., & O'Connor, C. (1987). Emotion knowledge: Further exploration

of a prototype approach. Journal of Personality and Social Psychology, 52,1061-1086.Smith, C., & Ellsworth, P. (1985). Patterns of cognitive appraisal in emotion. Journal of Personality

and Social Psychology, 48,813-838.Weller, S., & Romney, A. K. (1988). Systematic data collection. Beverly Hills, CA: Sage.

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