Affective and semantic priming: Effects of mood on category accessibility and inference

JOURNAL

OF EXPERIMENTAL

SOCIAL

PSYCHOLOGY

27, 480-498 (1991)

Affective and Semantic Priming: Effects of Mood on Category Accessibility and Inference RALPH ERBER University

of Virginia

When a person can be described by both a positive and a negative trait, a perceiver’s mood may influence which trait category is accessed for subsequent inferences about the person’s behavior. A positive mood should prime the positive trait category and activate knowledge associated with it. As a result, the person should be perceived as more likely to engage in behaviors implied by the positive trait category. Similar predictions can be made about the effects of negative mood. Two studies tested these hypotheses. In Study 1, positive, neutral, or negative moods were induced through exposure to brief stories with happy, neutral, or sad content. Then, in an allegedly unrelated experiment, subjects read about four stimulus persons, each described by a positive and a negative trait category (e.g., moody and warm), and rated the likelihood that the targets would engage in behaviors applicable to the positive trait, behaviors applicable to the negative trait, and behaviors that were simply positive and negative but not applicable to either trait. Positive mood increased the likelihood estimates of behaviors applicable to the positive trait category, while negative moods increased the likelihood estimates of behaviors applicable to the negative trait category. The likelihood estimates for behaviors nonapplicable to either trait category were unaffected by subjects’ mood. Study 2, using a facial feedback technique and using somewhat richer stimuli, replicated the findings of Study 1 for negative mood and suggests that the effect is mediated by moods increasing the accessibility of mood congruent trait categories. The implications of the results for research on category accessibility and on moods are discussed. o 19% Academic press, IIIC.

How we form impressions, make judgments, and arrive at inferences about other people often depends on how we perceive the person’s membership in social categories. Although having category systems to apply to the perception of others carries the risk of engaging in stereotypic overgeneralizations (e.g. Allport, 1954), they are nonetheless handy beThe first study reported in this paper was part of the author’s dissertation at Carnegie Mellon University and was presented at the 94th annual meeting of the American Psychological Association, Washington, DC, 1986. I thank Maureen Wang Erber, Susan Fiske, Stan Klein, Lenny Martin, and Carol Thomas for commenting on previous drafts of this paper. Address correspondence to Ralph Erber, Department of Psychology, DePaul University, 2219 N. Kenmore, Chicago, IL 60614. 480 0022-1031/91 $3.00 Copyright Q 1991 by Academic Press, Inc. All rights of reproduction in any form reserved.

AFFECTIVE

AND SEMANTIC

PRIMING

481

cause they enable perceivers to form impressions with little effort (Allport, 1954; Rosch, 1978). When the categories at hand are personality traits, one can make inferences about the presence of related traits, the absence of inconsistent traits, as well as the presence of representative behaviors with relative ease and speed. For example, when we know that a person is introverted, we can quickly infer that the person is likely to be shy, quiet, and avoid large social gatherings. A great deal of research has addressed the processes underlying categorization (e.g., Cantor & Mischel, 1979) and how we go about making trait inferences (e.g., Schneider, 1973). So far, little attention has been paid to how we form impressions of people who can be categorized by multiple traits. Others can frequently be categorized in terms of more than one trait and sometimes in terms of traits that are evaluatively but not descriptively inconsistent. For example, we can think of a colleague as critical and helpful. While this is not a terribly conflicting configuration of traits, our impression of her and our tendency to solicit her comments on our work depends on whether we think of her as primarily helpful or critical. This paper focuses on multiple category membership and attempts to show how our ongoing moods can influence which among several trait categories we choose as a basis for impressions and inferences. Previous research suggests two ways in which we can deal with the ambiguity presented by people who have seemingly inconsistent traits. First, a study by Asch and Zukier (1984) shows two strategies for the resolution of trait combinations that are evaluatively but not descriptively inconsistent. One strategy involves segregating the two traits by context relevance. For example, a person who is known to be nervous and reliable may be nervous when it comes to driving at night but reliable when it comes to borrowing books and computer software. Alternatively, the existence of the two traits can be attributed to a common source. By using this strategy, a perceiver can decide that another who is nervous and reliable might be anxious to please, which would explain both the nervousness and the reliability. Another line of research suggests that we can base our impressions on one trait more than another. Specifically, research on semantic priming has shown that we interpret ambiguous stimuli in terms of the trait category that is most accessible at the time the person is encountered (e.g., Wyer & Srull, 1986). Among the variables that have been shown to increase the accessibility of trait categories are the recency of priming (Bargh & Pietromonaco, 1982; Higgins & King, 1981; Higgins, King, & Mavin, 1982) and the frequency of priming (Srull & Wyer, 1979; 1980; Wyer & Srull, 1981). Both paradigms yield quite similar effects. Subjects use the primed categories to evaluate an ambiguous target, although it seems that the effects of frequency of activation predominate over the effects of recency of activation when there is a long delay between the

482

RALPH

ERBER

priming task and the judgment task (Higgins, Bargh, & Lombardi, 1985; Lombardi, Higgins, & Bargh, 1987; Wyer & Srull, 1986). Note that these effects have been obtained with trait categories that are evaluatively ano descriptively inconsistent. However, there is no reason to suspect that priming effects should not occur for trait categories that are evaluatively but not descriptively inconsistent. In both the frequency and recency paradigms priming is semantic, or conceptual in nature, because the accessibility of a trait category is increased through recent or frequent exposure to its semantic components (the category label in the recency paradigm and behavioral instances of the category in the frequency paradigm). However, trait categories may not be purely semantic representations but may also be imbued with affect (Allport, 1954; Fiske, 1982; Fiske, Neuberg, Beattie, & Milberg, 1987; Fiske & Pavelchak, 1986). That is, affect imbued with the category is stored in memory along with its label and attributes. Once a person is identified as a member of a category, inferences as well as affective responses to the person can be generated on the basis of category membership. For example, knowing that someone is hostile not only allows inferences about related traits (e.g., rudeness) and representative behaviors (e.g., a tendency to insult others), but can also provide a basis for an affective response (most likely negative) toward that person, especially when categorization is easy (Fiske et al., 1987). To the extent that category-related affect is stored along with other category relevant information, it may be that the process of “category-based affect” can operate in reverse. An affective state consistent with a category should increase the accessibility of its semantic components and as a result influence category-based judgments. In other words, it may be that categorization is not solely a function of the match between stimulus attributes and category but can also depend on the match between a perceiver’s affective state and the affective tone of an applicable category. Affect-based categorization, or affective priming, may be most easily obtained when the perceiver is in an affective state that closely corresponds to the affect imbued with the category. For example, if perceivers feel repulsed by people who are deceitful, being in a state of repulsion should increase access to the category “deceitful.” More diffuse affective states, such as moods, may also increase the accessibility of trait categories, perhaps because of their mere similarity in feeling tone. However, this process may operate best when moods are combined with a semantic cue. This hypothesis is suggested by the processing assumptions inherent in categorization. One view (Collins & Loftus, 1975; Anderson, 1983) holds that categories consist of a label to which attributes are linked in a probabilistic fashion. Categorization can be thought of as a process in which activation spreads from the category label to the attributes and vice versa. As the number of potential categories and their attributes increase, the

AFFECTIVE

AND SEMANTIC

PRIMING

483

relative amount of activation that each receives decreases (Anderson, 1983). Because people can be categorized in numerous ways (according to a multitude of traits, goals, gender, ethnicity, to name a few) positive and negative moods alone may simply not provide enough activation to prime any one of them sufficiently. Furthermore, since the spread of activation produced by moods is somewhat diffuse (Bower, 1981; Clark & Isen, 1982), one would expect that moods may best work as category primes when they are paired with a semantic cue. That is, to the extent that a person fits two categories that are imbued with positive and negative affect respectively, the perceiver’s affective state may increase the accessibility of the affectively congruent category. Everything else being equal, the perceiver’s affective state would serve as an additional source of priming that would increase the accessibility of the affectively congruent trait category. The idea that moods may influence categorization by increasing access to similarly toned social categories is further, yet indirectly, supported by research showing that moods bias a variety of social judgments in a mood congruent direction. Positive moods have been shown to increase people’s liking of their household appliances (Isen, Shalker, Clark, & Karp, 1978), their schools (Clark, Milberg, & Ross, 1983, Study 3) and others (Forgas & Bower, 1987). Being in a positive mood makes people feel more optimistic about the future and more positive about politics (Forgas & Moylan, 1987) whereas people in negative moods overestimate the risk of falling victim to personal and natural disasters (Johnson & Tversky , 1983). A number of studies show effects that could be due to either positive or negative moods. Subjects in negative moods tend to be less satisfied with their lives than people in positive moods (Schwarz & Clore, 1983; Strack, Schwarz, & Gschneidinger, 1985). Similarly, Forgas, Bower, and Krantz (1984) showed that happy subjects tended to see more positive than negative behaviors in a person perception task, while the opposite was true for subjects in a negative mood. According to one view (Bower, 1981; Clark & Isen, 1982), these effects come about because moods make affectively congruent material more accessible in memory leading to biases in the retrieval of information (e.g. Clark et al., 1983; Isen et al., 1978) as well as the encoding of new information (e.g. Bower, Gilligan, & Monteiro, 1981; Forgas & Bower, 1987; Niedenthal & Cantor, 1986; but see Schwarz & Clore, 1983, 1988, for a diverging account). In sum, the foregoing research suggests that moods may have priming capabilities not unlike those of semantic cues. Thus when subjects encounter a target who can be categorized in terms of both a positive and a negative trait, their mood should lead to categorization of the target in terms of the mood congruent category. This, in turn, should lead to an increased accessibility of information associated with the mood congruent

484

RALPH

ERBER

category and affect subsequent category relevant inferences. Inferences unrelated to either trait category should be affected by subjects’ mood to a lesser degree. These hypotheses were tested in the first study. STUDY 1 Method Overview Subjects participated in two allegedly unrelated, brief experiments that were run in one session. In the first study, subjects read short stories designed to induce a positive, neutral, or negative mood. In the second study, subjects read about four target persons described by both a positive and a negative trait and then rated the likelihood that the targets would engage in positive and negative behaviors that were either applicable to the traits or not.

Subjects Forty-two Carnegie Mellon University undergraduates (29 males and 13 females) participated as part of a course requirement. Subjects were run in noninteracting groups of two to four. Each subject was randomly assigned to conditions with the stipulation that there be equal cell frequencies.

Procedure Upon arrival at the laboratory, subjects seated themselves in one of four cubicles. After all subjects were seated, the first experimenter explained that the experimental session involved two short but unrelated experiments that were being run together primarily because they were very brief. The first experiment was a study on text comprehension and the second study a short pretest on impression formation. The first experimenter then explained his study. He was interested in issues concerning the comprehension of case study information. He added that there were various ways in which case study information could be presented, and that the purpose of his experiment was to determine which format was most comprehensible. For that reason, he had created several versions of a case study. Subjects were asked to read the case to achieve a good understanding of it so they would be able to answer a number of questions later on. Induction of mood. Subjects received one of three stories describing events that happened to a young, female artist. The story for subjects in the positive mood condition described a number of fortunate events that culminated in her receiving a scholarship to study art. The story, designed to induce a negative mood, described how the same person was overcome by a rare, disabling illness (rheumatoid arthritis) at the end of her freshman year in college. The neutral mood story simply described how the person decided which college to attend. All three stories were approximately the same length.’ After subjects finished reading the stories, the first experimenter explained an additional reason for conducting the two experiments in one session. Because a delay between reading text and answering questions was common in the study of text comprehension, subjects would complete the impression formation pretest before finishing the text comprehension study. He then left the room to get the second experimenter who introduced himself as a research assistant working on a project dealing with how people form impressions of others when the only information available concerns personality characteristics. He added that the session was merely a pretest designed to develop materials to be used in a future experiment. I Copies of all three stories are available from the author.

AFFECTIVE

AND SEMANTIC

PRIMING

485

Each subject was then given a folder containing the stimulus materials and the dependent measures. Stimulus materials. Each folder contained four 3 x 5 index cards describing four different target persons in terms of two personality traits, one of which was positive and the other negative. Each card consisted of the target’s name and the combination of traits (e.g., “Pat is described as moody and warm”). The trait labels were selected from Anderson’s (1968) list of likability ratings for 555 personality traits. Initially, 10 highly positive and 10 moderately negative traits were selected from the meaningful traits and likableness ratings were collected from 20 undergraduates. The positive traits were chosen from among the 40 most favorable traits. Their likableness rankings ranged from 469 to 529. The negative traits represent rankings higher than the bottom 40. That is, while the positive traits were extremely positive, the negative traits were only moderately negative. This was done because negative information has been shown to receive more weight than positive information in impression formation (Fiske, 1980). Thus, although the negativity of the negative traits does not parallel the positivity of the positive traits, they should be similar in their psychological impact. This pretest eliminated a total of eight traits that were judged as either too negative or as not positive enough. The remaining six positive and six negative traits were combined in all possible ways and the combinations were pretested regarding their likelihood of cooccurrence. Fifteen undergraduates rated the likelihood that a person would have both traits using a 9-point scale with the endpoints “not at all likely” and “extremely likely.” Based on these ratings four trait combinations of moderate a priori likelihood were selected: “moody and warm” (M = 5.25) “understanding and pessimistic” (M = 4.55), “unselfish and unsociable” (M = 4.90) and “trustworthy and possessive” (M = 5.60). A second set was created by reversing the order of the traits in each combination. Each subject received a set of four 3 X 5 index cards containing the four trait combinations. Each set contained two trait combinations with the positive trait first and two with the negative trait first. The order of the combinations within sets was randomized. Dependent measures. Along with the set of index cards, subjects received a set of questionnaires about the likelihood that each target would engage in four different behaviors. One of the behaviors was applicable to the positive trait category (e.g., “Welcomes a friend with a hug” for the category “warm”) and one of the behaviors was applicable to the negative trait category (e.g., “Gets depressed over the weather” for the category “moody”). The remaining behaviors were simply positive and negative and not applicable to either one of the trait categories? Table 1 shows the list of traits, the corresponding applicable behaviors, the nonapplicable behaviors, and the valence of the traits and behaviors. Subjects rated the likelihood of each of these behaviors on 9-point scales with the endpoints “not at all likely” and “extremely likely.” The order of the questionnaires corresponded to the order in which the target persons were presented. Within each questionnaire, the order of the applicable and nonapplicable behaviors was randomized. After subjects had completed the likelihood estimates, the first experimenter returned and handed out a “Text Comprehension Questionnaire” which consisted of three questions. Subjects were then asked to describe the main event that happened to the person whose case study they had read. In addition, they were asked to describe three other “elements of the story.” The final question served as a manipulation check for the effectiveness of the mood induction. Subjects were asked to indicate how the story made them feel on a 9-point scale with the endpoints “negative, depressed,” and “positive, uplifted.” Upon completion of this questionnaire, subjects were probed for suspicion and fully debriefed. None of the subjects was able to guess the experimenter’s hypothesis. ’ The dependent measures were obtained by having 20 undergraduates generate behaviors consistent with the trait categories listed above. To obtain positive and negative nonapplicable behaviors, subjects were asked to list behaviors typical for the traits clever, humorous, creative, reliable, clumsy, untidy, stubborn, and nosey.

486

RALPH

ERBER

TABLE TRAIT

COMBINATIONS,

VALENCE

Traits

Valence

Understanding

+

Pessimistic

-

Warm

+

Moody

-

Trustworthy

+

Possessive

-

Unselfish

+

Unsociable

-

OF TRAITS,

Applicable

1 AND

DEPENDENT

behaviors

MEASURES

(STUDY

Nonapplicable

1)

behaviors

Not get upset about a friend who yells Not ask a girl out for a date

Tell a joke to liven up a party Refuse to admit that he is wrong

Welcome a friend with a hug Get depressed over the weather

Debug a computer program Lock the keys in the car

Not cheat on an exam when teacher steps out Call her boyfriend every day Volunteer for the clean-up committee Prefer running over team sports

Write poetry for the school paper Leave cigarette butts on the floor Be prompt for appointments and dates Read roommate’s letter to her boyfriend

Results Manipulation Check

Subjects’ responses to the manipulation check were submitted to a oneway analysis of variance with mood (positive, neutral, negative) as the between-subjects factor. The analysis was highly significant: F(2, 39) = 56.39, p < .OOOl. The means for the positive and neutral story were 7.50 and 6.29, respectively. The mean for the negative story was 2.50. Likelihood Estimates

Subjects’ likelihood estimates of the four behaviors were averaged across the four stimulus replications to obtain single indices for the applicable (positive/negative) and the nonapplicable (positive/negative) behaviors. These indices were then submitted to a three-way analysis of variance with type of mood as between-subjects factor and applicability and valence of the behaviors as within-subjects factors.3 This analysis revealed two effects. First, there was a main effect for applicability, such 3 Prior to averaging subjects’ likelihood estimates across targets, the same analysis was performed using stimulus replication as a within-subjects factor. Somewhat unexpectedly, this analysis revealed an interaction among mood, applicability, and stimulus replication. However, an inspection of the means indicated that the interaction came from two deviant means. That is, 22 out of 24 means fell into the same pattern. Because of this tendency it seemed justified to average across stimulus replications.

AFFECTIVE

AND SEMANTIC TABLE

MEAN

LIKELIHOOD

ESTIMATES

FOR APPLICABLE

487

PRIMING

2 AND

NONAPPLICABLE

BEHAVIORS

AS A

RESULT OF Moor Mood Positive

Neutral

Negative

Applicable behaviors Positive Negative

1.46,, 6.86,b

6.30, 7.35.k

6.34, 8.16,

Nonapplicable Positive Negative

4.60 4.11

5.07 4.00

4.23 3.64

behaviors

Note. n = 14. Means not sharing subscripts differ significantly at p < .05.

that the applicable behaviors received higher ratings than the nonapplicable behaviors (M = 7.08 and 4.28, respectively) regardless of their valence: F(1, 117) = 282.36, p < .OOOl. Although not directly relevant for the test of the mood hypothesis, this effect indicates that subjects did in fact use the trait categories to make their judgments. The second effect obtained from the analysis was an interaction among all three factors: F(2, 117) = 5.35, p < .Ol. Table 2 depicts the means for this analysis. As predicted, subjects in a positive mood rated the positive applicable behaviors as more likely than subjects in a neutral or negative mood. Conversely, subjects in a negative mood rated the negative applicable behaviors as more likely than subjects in a neutral or positive mood. Also as predicted, subjects in the positive mood condition rated the likelihood of the positive applicable behaviors higher than the likelihood of the negative applicable behaviors while the reverse was true for subjects in the negative mood condition. As the bottom two rows indicate, this pattern of means does not hold true for the nonapplicable behaviors. An analysis of simple effects using the computational procedures outlined by Kirk (1968) confirmed the above interpretation of the results. Specifically, there was a significant two-way interaction between mood and valence within the applicable behaviors, F(2, 117) = 10.48, p < .Ol, while no such interaction was observed within the nonapplicable behaviors, F(2, 117) = .70. The simple effects analysis was followed by NewmanKeuls myltiple comparisons among the likelihood estimates for the applicable behaviors. The outcomes of these comparisons partially confirmed both sets of predictions about the effects of moods on the likelihood estimates of positive and negative applicable behaviors. First, subjects in a positive mood gave higher likelihood ratings for the positive applicable behaviors (M = 7.46) than subjects in the neutral mood condition (M = 6.30, p < .05). However, there was no difference within-subjects in the

488

RALPH

ERBER

positive mood condition for the likelihood estimates of positive applicable behaviors vs. negative applicable behaviors (M = 7.46 vs M = 6.86, n.s.). This pattern was reversed for comparisons involving negative mood. The ratings of the negative applicable behaviors were not significantly higher in the negative mood condition (M = 8.16) than in the neutral mood condition (M = 7.35). However, they were significantly higher than the ratings of the positive applicable behaviors (M = 6.34, p < .05). Discussion The results of Study 1 provide some evidence for the hypotheses concerning the effects of moods on likelihood estimates of behaviors that are applicable to trait categories. Positive mood and negative mood had somewhat different effects. Positive mood increased likelihood estimates of positive applicable behaviors compared to neutral mood. Negative mood increased likelihood estimates of negative applicable behaviors compared to positive applicable behaviors. The likelihood estimates for behaviors nonapplicable to either trait were not affected by the mood manipulations and were generally lower than the likelihood estimates for applicable behaviors. Besides lending support to the central hypothesis of this paper, the results of Study 1 raise a number of issues. The first issue concerns the interpretation of the effect as mediated by the increased accessibility of mood congruent trait categories. There is some indirect evidence for such an account. First, the fact that mood only interacted with the valence of the applicable behaviors and that on average the nonapplicable behaviors were rated significantly lower than the applicable behaviors suggests the strong inference that the trait categories were indeed crucial for the effect. On the other hand, subjects made ratings about the likelihood of behaviors applicable and nonapplicable to the trait categories. However, unlike reaction times or recall, such a measure does not provide direct evidence for the effects being caused by differential access to trait categories. The strong inference is further complicated by the nature of the target descriptions. One could argue that the main effect for applicability may be an artifact due to the nature of the stimulus materials. That is, to the extent that the stimuli were described solely in terms of two trait adjectives, there may have been some demand on subjects to give higher likelihood estimates to those behaviors that were related to the traits than those behaviors that were obviously unrelated. The way moods were induced in the first study could also be problematic for the interpretation of the results. Both the mood inductions and the dependent measures were semantic in nature, and thus one could argue that the effects could be due to the semantic effects of the stories (expectations about positive and negative events) rather than their emotional impact per se.

AFFECTIVE

AND SEMANTIC

PRIMING

489

A final and related issue concerns the generalizability of the results obtained in Study 1. One could argue that the observed effects are limited to situations in which only trait information is available. That is rarely the case in real life. Instead, we usually have information about a variety of others’ characteristics, traits being just some of many. One may therefore ask whether the effects of Study 1 can be replicated with richer, more realistic stimuli, that is, stimuli containing information irrelevant to the judgments. All three issues are addressed in Study 2. It uses a different, nonsemantic mood manipulation and target descriptions containing irrelevant information in addition to the trait information. It also includes a measure of trait recall to substantiate the theoretical claims regarding the mediation of the judgment effects. STUDY 2 Method Overview Study 2 is identical to Study 1 except for the following changes. First, a facial feedback procedure similar to the one used by Strack, Martin, & Stepper (1988) was substituted for the mood manipulation. Second, information irrelevant to the judgments was added to all stimulus replications. Specifically, information about the targets’ hometown, major, and extracurricular activities was added to the stimulus material to make it more realistic and to decrease the salience of the trait adjectives. Third, in Study 1 the negative applicable behaviors received higher likelihood estimates than the positive applicable behaviors, with the reverse being true for the nonapplicable behaviors. A postexperimental ratings task revealed that in both cases these differences were accounted for by one deviant behavioral item. These items and the corresponding traits were eliminated for Study 2 and the trait combinations were rearranged, which resulted in three stimulus replications instead of the four used in Study 1.

Subjects Forty-five undergraduates from the University 21 undergraduates from Trinity University (15 experiment for extra course credit. Subjects were of two to four, and each subject was randomly

of Georgia (35 females and 10 males) and females and 6 males) participated in the run individually or in noninteracting groups assigned to conditions.

Procedure After subjects arrived, the experimenter introduced the experiment as being concerned with ways to make it easier for handicapped students to participate in psychology experiments. He explained that various types of handicaps made it hard on handicapped students to complete the paper and pencil tasks so common in experiments. He went on to say that paper and pencil tasks are an especially big hurdle for students who have no use of their hands and that it was the goal of the present study to find ways for such students to do paper and pencil tasks in an alternative way. After this general introduction, the experimenter explained that one alternative way of writing was to hold a pen in one’s mouth instead of one’s dominant hand. He held up a picture from a newspaper article depicting an artist drawing with a pen in his mouth and said that he wanted to find out which of several ways of holding a pen in one’s mouth would be best for marking questionnaires. Two techniques would be tried out. Subjects

490

RALPH ERBER

were to hold the pen either lightly between their teeth or tightly between their teeth. The experimenter emphasized that it was important that the pen not touch subjects’ lips and demonstrated each technique. He then explained that the subjects in the present session were in a control condition in which they could do the task with their dominant hand. However, to make the control condition as comparable as possible to the “experimental conditions,” subjects were to hold a rolled-up paper towel between their teeth for the duration of the experiment. He demonstrated the techniques one more time and then randomly assigned subjects to one of three conditions: light teeth, tight teeth, and dominant hand. In the light teeth condition subjects’ facial expressions simulated the expression typically associated with happiness. In the tight teeth condition, subjects’ facial expressions simulated the expression typically associated with anger. The dominant hand condition served as a neutral affect control condition. Experimental subjects were asked to keep the paper towel between their teeth for the duration of the experiment. The effectiveness of these manipulations of subjects’ affect was ascertained in an independent study conducted concurrently with the present one (Strack, Martin, Harlow, & Stepper, 1989, Study 2). Subjects in the three conditions were presented with the description of a typical college prank and were asked to indicate how funny or mean they perceived the prank to be. Subjects in the light teeth condition thought the prank was funnier than subjects who read and responded to the description while holding the pen in their dominant hand. At the same time, subjects in the tight teeth condition thought the prank was meaner than did subjects in the dominant hand condition. Based on these results (obtained in part on the same subject population) it was concluded that the facial feedback manipulations successfully induced the desired affective states. Stimu1u.s materiuls. Subjects received a packet describing three target persons. The first page of the packet instructed subjects to read descriptions of several people and then answer a number of questions about them. Each description contained information about the target’s hometown, major, year in school, and extracurricular activities along with a combination of a positive and a negative trait adjective. The following combinations were used: warm and moody, understanding and unsociable, and trustworthy and possessive. Following is an example of one target description: Pat is a freshman in H&SS who is thinking about majoring in history. He grew up in Atlanta, Georgia. Pat recently became a pledge of one of the fraternities on campus. He likes going to movies and listening to music. People who know him describe him as moody and warm. In an attempt not to confound the trait information with the rest of the descriptions, the trait pairs rotated through the irrelevant information (i.e., hometown, major, etc.) according to a latin square.4 As in the previous study, whether subjects received the positive or the negative trait first was randomized. Dependent measures. Subjects rated the likelihood that each target would engage in four different behaviors. One of the behaviors was applicable to the positive trait category, one was applicable to the negative trait category, and the remaining two behaviors were simply positive and negative, but unrelated to either trait. The order in which the four behaviors appeared on the questionnaires was randomized according to a modified latin square. The last page in the packet asked subjects to write down everything they remembered about 4 While the irrelevant pieces of information rotated through the descriptions, of the targets were always paired with the same pair of trait adjectives. Whereas that people think people from Atlanta are generally warmer than the average seems less likely that subjects would think of the common first names used in (Pat, Rick, and Bob) as systematically associated with the traits.

the names it may be person, it this study

AFFECTIVE

AND SEMANTIC TABLE

MEAN

LIKELIHOOD

ESTIMATES

FOR APPLICABLE OF PEN

491

PRIMING

3

AND NONAPPLICABLE POSITION

BEHAVIORS

AS A RESULT

Pen position Light teeth

Dominant hand

Tight teeth

Applicable behaviors Positive Negative

6.73,, 5.91&

6.&b, 6.52,,

5.44, 7.26,

Nonapplicable Positive Negative

4.35 3.90

3.52 4.14

3.65 4.15

behaviors

Note. n = 22. Means not sharing subscripts differ significantly at p < .05. the three people they rated in the order in which it occurred to them. Subjects did this separately for each target, and the order in which the targets were listed on the recall sheet was always different from the order in which they had initially been presented.

Results Likelihood Estimates

As in Study 1, subjects’ likelihood estimates for the four behaviors were averaged across stimulus replications to obtain single indices for the applicable (positive/negative) and the nonapplicable (positive/negative) behaviors. These indices were then submitted to a three-way analysis of variance with position of pen (light teeth, tight teeth, dominant hand) as between-subjects factors and applicability (yes/no) and valence of the behaviors (positive/negative) as within-subjects factors. The analysis showed that the experiment successfully replicated the effects observed in Study 1. Once again, there was a main effect for applicability. That is, the likelihood estimates for the applicable behaviors were on average higher (M = 6.35) than for the nonapplicable behaviors (M = 3.95): F(1, 189) = 253.45, p < .OOl. More importantly, the interaction among all three factors was once again obtained: F(2, 189) = 3.20, p < .05. Table 3 depicts the means for this analysis. Once again it appeared that the likelihood estimates of the applicable behaviors were affected by the experimental manipulations while the ratings of the nonapplicable behaviors seemed to be relatively unaffected. An analysis of simple effects indicated that this was an appropriate way to interpret the pattern of means. Specifically, there was a significant twoway interaction between mood and valence within the applicable behaviors, F(2, 189) = 12.0, p < .Ol, while only a marginally significant interaction was observed within the nonapplicable behaviors: F(2, 189) = 2.74, p < .lO. The simple effects analysis was followed by Newman-Keuls

492

RALPH ERBER TABLE AVERAGE

NUMBER

4

OF POSITIVE AND NEGATIVE TRAITS RECALLED PEN POSITION

AS A RESULT OF

Pen position Traits Positive Negative

Light teeth

Dominant hand

Tight teeth

1.46,, 1.64,

1.73, 1.96,

1.09, 2.00,

Note. Range: 0 to 3. Means not sharing subscripts differ significantly at p < .OS.

multiple comparisons among the likelihood estimates of the applicable behaviors. They showed the following results. Between conditions, the likelihood estimates for positive applicable behaviors were higher in the light teeth condition (M = 6.73) than in the tight teeth condition (M = 5.44): p < .05. The reverse was true for the likelihood estimates of negative applicable behaviors (M = 7.26 and 5.91: p < .05). Within the tight teeth condition, the likelihood estimates of negative applicable behaviors were higher (M = 7.26) than the likelihood estimates of positive applicable behaviors (M = 5.44): p < .Ol. No within-subjects differences were found in the light teeth and dominant hand condition. Recall of Traits

The recall sheet at the end of each package was scored according to how many of the positive and negative target traits subjects remembered. The average number of traits recalled was then submitted to a two-way analysis of variance with position of pen as between-subjects factor and valence of trait as within-subjects factor. The analysis revealed two significant effects. First, on average subjects recalled more negative traits (M = 1.86) than positive traits (M = 1.42): F(1, 63) = 13.62, p < .OOl. However, this main effect was qualified by a significant interaction between position of pen and valence of trait: F(2, 63) = 3.90, p < .05. The means for this analysis are depicted in Table 4. Newman-Keuls multiple comparisons indicated that subjects in the tight teeth condition recalled significantly fewer positive traits (M = 1.09) than subjects in the dominant hand condition (M = 1.73) and subjects in the light teeth condition (M = 1.46): both ps < .05. At the same time, subjects in the tight teeth condition recalled more negative traits (M = 2.00) than positive traits (it4 = 1.09): p < .Ol. Correlations between Likelihood Estimates and Recall To gain insight into the extent to which the likelihood estimates might be associated with differential access to the trait categories Pearson Product-Moment correlations between the likelihood estimates of the positive

AFFECTIVE

AND SEMANTIC

PRIMING

493

and negative applicable behaviors and recall of the positive and negative traits were computed for each of the experimental conditions separately. The likelihood estimates of the negative applicable behaviors were significantly correlated with recall of negative traits in the tight teeth condition (r = .52, p < .05) but not in the light teeth condition or the dominant hand condition. The likelihood estimates of the positive applicable behaviors were not correlated with recall of positive traits in any of the conditions. GENERAL

DISCUSSION

Study 2 successfully replicates the results of Study 1. A very different manipulation of affect resulted in an interaction similar to the one obtained in the first study. The manipulation of subjects’ facial expressions once again affected the likelihood estimates of behaviors applicable to positive and negative trait categories but not behaviors nonapplicable to either trait. Specifically, subjects whose facial expression resembled that of anger gave higher ratings to behaviors applicable to a negative trait category than to behaviors applicable to a positive trait category. In addition, the positive affect (light teeth) condition elicited higher ratings for positive applicable behaviors compared to the negative affect (tight teeth) condition. At the same time, the negative affect condition elicited higher ratings for negative applicable behaviors compared to the positive affect condition. The only finding that did not replicate was the previously observed difference between the ratings of the positive applicable behaviors in the positive mood and neutral mood condition. Apart from replicating the previous findings, Study 2 shows that the affect manipulation impacted on the recall of affect congruent traits. Specifically, subjects in whom negative affect had been induced recalled significantly more negative traits than positive traits. In addition, in the negative affect condition, recall of negative traits was correlated with the likelihood estimates of negative behaviors applicable to those traits. This latter finding corroborates the hypothesis that the effects of negative mood on inferences about negative applicable behaviors were indeed due to the increased accessibility of the negative trait categories. It is worth pointing out that while the effects of negative moods were specific to the trait categories primed along with the mood, they were not specific to the particular negative moods induced. Remember that the negative story in Study 1 induced a sad, depressed mood. The affective state induced by the pen manipulation in Study 2, on the other hand, is more akin to anger (Martin et al., 1989). Nevertheless, both manipulations had almost identical effects. This finding suggests that the negative affect “attached” to negative social categories is diffuse, and that all it takes to increase the accessibility of a given category is a match in the general feeling tone rather than any specific mood or emotion.

494

RALPH

ERBER

It appears that the effects of positive mood were somewhat different from the effects of negative mood. Specifically, positive mood affected the likelihood judgments of positive applicable behaviors compared to the neutral mood condition (in Study 1) and the negative affect condition (in Study 2). Thus, the effects on positive applicable behaviors were found ucro’ossmood conditions. Negative mood, on the other hand, also affected the likelihood judgments within conditions. That is, the likelihood estimates of the negative applicable behaviors increased relative to the likelihood estimates of the positive applicable behaviors. Furthermore, negative affect in Study 2 led to an increase in recall of negative trait categories, and this increase in recall was associated with an increase in the likelihood estimates of the behaviors applicable to those traits. Comparable effects were not obtained for positive affect. A rigorous interpretation of this pattern of results suggests that the effects of negative affect on the likelihood judgments were most likely due to negative affect increasing the accessibility of the negative trait categories. The same cannot unequivocally be said for the effects of positive moods because of the absence of within-subjects differences and the lack of any differential recall of positive traits. The finding that the effects of negative mood were more in line with the predictions than the effects of positive mood is interesting in light of the often observed asymmetry of mood effects. Past research on moods (e.g. Clark et al., 1983; Forgas & Moylan, 1987; Isen et al., 1978) has consistently found effects for positive mood while negative mood has often failed to yield mirror image results. Faced with this asymmetry, Isen (1984) concluded that the effects of negative mood are more “complex.” The present studies suggest one way in which this complexity emerges. Unlike previous research, which has primarily looked at the direct effects of moods on social judgments, the present studies combine moods with judgment-relevant, congruent semantic cues. It appears from the present data that negative moods may affect information processing and social judgments best when combined with additional semantic cues. How can one account for the relatively weaker effects of positive mood in the present studies ? Of course, it could be that the negative mood manipulations in both studies were simply more impactful than the manipulations of positive mood. In fact, there is some evidence that this may have been the case in the first study. Specifically, the positive story elevated subjects 1.2 points above the neutral subjects whereas the negative story lowered subjects 3.79 points. However, the same explanation cannot easily be applied to the results of the second study given the symmetrical effects of the manipulations reported by Martin, Strack, Harlow, and Stepper (1989). Thus, an interpretation of the present findings in terms of differences in the impact of the mood manipulations remains inconclusive. Alternatively, it may be that the findings for positive mood are due to

AFFECTIVE

AND SEMANTIC

PRIMING

495

a “fan effect” operating at retrieval. Since the majority of our experiences tend to be positive, it may be that our representations of positive material are more elaborate with more pathways among more memory nodes than our representations of negative material. As a result, the relative activation received by any one node becomes less strong as the number of nodes and pathways increases (Anderson, 1983). Thus it may be that moodstate-dependent retrieval of positive material in memory unrelated to the categorization and judgment task decreased the amount of activation to the category relevant information and thus led to the relatively weaker results for positive mood. Admittedly, this explanation is somewhat speculative and it remains for future research on the information processing differences between positive and negative mood to bear it out. Another issue deserving of further research concerns the question of when in the information processing sequence the mood effects occur. The present model proposed that, just like semantic primes, moods would have their effects when the target is first encountered. That is, they make category-relevant material more accessible in memory and in this way bias later judgments and inferences. The negative mood results of both studies are certainly consistent with this model. However, since subjects experienced their moods both when they encountered the target description and when they made their judgments, it is not clear whether mood exerted its influence primarily during the initial categorization of the target or during the judgment phase. Note that this is not an issue of whether accessibility mattered, instead it is one of when it mattered. Thus, the interpretation of the present findings in terms of increased accessibility of material related to the mood congruent trait does not hinge on the ability to distinguish between the two possibilities. However, it is worthy of further experimental disentanglement. If one adopts the view that mood had its effect when the ambiguous target was first encountered, exactly how did the priming effects in the present studies come about? Again, there are several possibilities. First, the priming of mood may lead to a more thorough processing of the mood congruent trait. Second, the mood priming may have facilitated the processing of the mood congruent trait. If the former is true one would expect longer processing times for mood congruent material, if the latter were the case one would expect shorter processing times. The present studies were not designed to distinguish between these possibilities. However, previous research (e.g. Forgas & Bower, 1987) has shown that subjects spend more time encoding mood congruent information, thus lending support to the idea that mood results in more thorough processing of mood congruent information. Relationship to Previous Research on Affect and Person Perception

The results of the present studies add to previous research on mood and person perception in important ways. In a conceptually similar study,

RALPH ERBER

496

Forgas and Bower (1987) supplied subjects in whom either a positive or negative mood had been induced with descriptions containing both positive and negative information about several targets. The descriptions were designed to communicate information “about the two most common dimensions found in person perception research, namely, likability and competence” (Forgas & Bower, 1987, p. 54). Subsequently subjects rated the targets on a number of dimensions, some of which were related to likability and competence and others that were among the most common in person perception tasks. The results showed a global increase in the number of judgments as a function of subjects’ mood. That is, subjects made more positive than negative judgments when they were in a positive mood but more negative than positive judgments when they were in a negative mood. One could argue that these global effects of mood are somewhat at odds with the more specific effects found in the present studies. However, such a conclusion would be premature. Forgas and Bower’s (1987) trait descriptions were designed to convey a global impression and thus mood had global effects. In contrast, the trait descriptions in the present research were specific with regard to a set of behaviors and thus mood had specific effects. In essence, the combined message from the present work and that of Forgas and Bower is that mood can have specific as well as global effects. Which one it will have may depend on the nature of the semantic material (global vs specific) that is primed along with the mood. The results of the present studies add to our knowledge about the relationship between affect and categorization in an important way. Fiske et al. (1987) have shown that affective responses to a stimulus can depend on the match between stimulus features and a category. The present research suggests that this process may in fact operate in reverse. That is, categorization can also depend on the rough match between a perceiver’s affective state and the affective tone of a social category. This seems to be especially true for the relationship between negative affect and negative social categories. Thus, the present research may have important implications for the understanding of stereotyping, which has been conceptualized as an inevitable consequence of social categorization (e.g., Allport, 1954). It may be that negative affect facilitates stereotypic responses because of its propensity to increase the accessibility of negative social categories. REFERENCES Allport, G. W. (1954). The nature of prejudice. Reading, MA: Addison-Wesley. Anderson, J. R. (1983). A spreading activation theory of memory. Journal of Verbal Learning and Behavior, 22, 261-295. Anderson, N. H. (1968). Likableness ratings of 5.55 personality-trait words. Journal of Personality

and Social

Psychology,

9, 272-279.

AFFECTIVE

AND SEMANTIC

PRIMING

497

Asch, S. E., & Zukier, H. (1984). Thinking about persons. Journal of Personality and Social Psychology, 46, 1230-1240. Bargh, J. A., & Pietromonaco, P. (1982). Automatic information processing and social perception: The intluence of trait information presented outside of conscious awareness on impression formation. Journal of Personality and Social Psychology, 43, 437-449. Bower, G. H. (1981). Mood and memory. American Psychologist, 36, 12-48. Bower, G. H., Gilligan, S. G., & Monteiro, K. P. (1981). Selectivity of learning caused by affective states. Journal of Experimental Psychology: General, 110,451-473. Cantor, N., & Mischel, W. (1979). Prototypes in person perception. In L. Berkowitz (Ed.), Advances in experimental social psychology (Vol. 12). New York: Academic Press. Clark, M. S., & Isen, A. M. (1982). Toward understanding the relationship between feeling states and social behavior. In A. Hastorf & A. M. Isen (Eds.), Cognitive social psychology. New York: Elsevier North-Holland. Clark, M. S., Milberg, S., & Ross, .I. (1983). Arousal cues arousal-related material in memory: Implications for understanding effects of mood on memory. Journal of Verbal Learning

and Verbal

Behavior,

22, 633-649.

Collins, A., & Loftus, E. S. (1975). A spreading activation theory of semantic processing. Psychological

Review,

82, 407-428.

Fiske, S. T. (1980). Attention and weight in person perception: The impact of negative and extreme behavior. Journal of Personality and Social Psychology, 38, 889906. Fiske, S. T. (1982). Schema-triggered affect: Applications to social perception. In M. S. Clark & S. T. Fiske (Eds.), Affect and cognition: The seventeenth annual Carnegie Symposium on affect and cognition. Hillsdale, NJ: Erlbaum. Fiske, S. T., Neuberg, S. L., Beattie, A. E., & Milberg, S. (1987). Category-based and attribute-based reactions to others: Some information on conditions of stereotyping and individuating processes. Journal of Experimental Social Psychology, 23, 399-427. Fiske, S. T., & Pavelchak, M. A. (1986). Category-based versus piecemeal based affective responses: Developments in schema-triggered affect. In R. M. Sorrentino & E. T. Higgins (Eds.), The handbook of motivation and cognition: Foundations of social behavior. New York: Guilford Press. Forgas, J. P., & Bower, G. H. (1987). Mood effects on person-perception judgments. Journal of Personality

and Social

Psychology,

53, 53-60.

Forgas, J. P., Bower, G. H., & Krantz, S. (1984). The influence of moods on perceptions of social interactions. Journal of Experimental Social Psychology, 20, 497-513. Forgas, J. P., Moylan, S. (1987). After the movies: Transient moods and social judgments. Personality

and Social

Psychology

Bulletin,

W, 467-477.

Higgins, E. T., Bargh, J. A., & Lombardi, W. (1985). Nature of priming effects on categorization. Journal of Experimental Psychology: Memory, Learning and Cognition, 11, 59-69. Higgins, E. T., & King, G. (1981). Accessibility of social constructs: Information processing consequences of individual and contextual variability. In N. Cantor & J. F. Kihlstrom (Eds.), Personality, cognition, and social interaction. Hillsdale, NJ: Erlbaum. Higgins, E. T., King, G., & Mavin, G. H. (1982). Individual construct accessibility and subjective impressions and recall. Journal of Personality and Social Psychology, 43, 3547. Higgins, E. T., Rholes, W. S., & Jones, C. R. (1977). Category accessibility and impression formation. Journal of Experimental Social Psychology, 13, 141-154. Isen. A. M. (1984). Toward understanding the role of affect in cognition. In R. S. Wyer & T. K. Srull (Eds.), Handbook of social cognition, Vol. 3. Hillsdale, N.J.: Erlbaum. Isen, A. M., & Levin, P. F. (1972). The effect of feeling good on helping: Cookies and kindness. Journal of Personality and Social Psychology, 21, 386388.

498

RALPH ERBER

Isen, A. M., ShaIker, T., Clark, M. S., & Karp, L. (1978). Affect, accessibility of material in memory and behavior: A cognitive loop? Journal of Personality and Social Psychology, 36, 1-12. Johnson, E. J., & Tversky, A. (1983). Affect, generalization, and the perception of risk. Journal of Personality and Social Psychology, 45, 20-31. Kirk, R. E. (1968). Experimental design: Procedures for the behavioral sciences. Belmont, CA: Wadsworth. Lombardi, W. J., Higgins, E. T., & Bargh, J. A. (1987). The role of consciousness in priming effects: Assimilation versus contrast as a function of the priming task. Personality and Social Psychology Bulletin, l3, 411-429. Martin, L. L., Strack, F., Harlow, T. F., & Stepper, S. (1989). Expressions, awareness, and emotions: Evidence for a “direct categorical facial feedback”. Manuscript under review. Niedenthal, P. M., & Cantor, N. (1986). Affective responses as guides to category-based inferences. Motivation and Emotion, 10, 31-46. Rosch, E. (1978). Principles of categorization. In E. Rosch & B. B. Lloyd (Eds.), Cognition and categorization. Hillsdale, NJ: Erlbaum. Schneider, D. J. (1973). Implicit personality theory: A review. Psychological Bulletin, 79, 294-309.

Schwarz, N., & Clore, G. L. (1983). Mood, misattribution, and judgments of well-being: Informative and directive functions of affective states. Journal of Personality and Social Psychology, 45, 513-523. Schwarz, N., & Clore, G. L. (1988). How do I feel about it? The informative functions of affective states. In K. Fiedler & J. P. Forgas (Eds.), Affect, cognition andsocial behavior. Toronto: Hogrefe. Srull, T. K., & Wyer, R. S. (1979). The role of category accessibility in the interpretation of information about persons: Some determinants and implications. Journal of Personality and Social Psychology, 37, 1660-1672. Srull, T. K., & Wyer, R. S. (1980). Category accessibility and social perception: Some implications for the study of person memory and interpersonal judgments. Journal of Personality and Social Psychology, 38, 841-856. Strack, F., Martin, L. L., & Stepper, S. (1988). Inhibiting and facilitating conditions of the human smile: A nonobtrusive test of the facial feedback hypothesis. Journal of Personality

and Social

Psychology,

54, 768-777.

Strack, F., Schwarz, N., & Gschneidinger, E. (1985). Happiness and reminiscing: The role of time perspective, affect, and mode of thinking. Journal of Personality and Social Psychology, 49, 1460-1469. Wyer, R. S., & Srull, T. K. (1981). Category accessibility: Some theoretical and empirical issues concerning the processing of social stimulus information. In E. T. Higgins, C. P. Herman, & M. P. Zanna (Eds.), Social cognition: The Ontario Symposium. (Vol. 1). Hillsdale, NJ: Erlbaum. Wyer, R. S., & Srull, T. K. (1986). Human cognition in its social context. Psychological Review,

93, 322-359.