written versus visual stimuli in the study of impression formation

Written versus visual stimuli in the studyof impression formation

Lisa Slattery Rashotte *

Department of Sociology and Anthropology, University of North Carolina, Charlotte,

9201 University City Boulevard, Charlotte, NC 28223, USA

Abstract

An Affect Control Theory approach is applied to the question of what information people

receive and use in forming impressions when observing written versus visual stimuli. Two iden-

tical sets of social events involving actors, objects, and behaviors were created. These two sets

of events, one in written form and one on videotape, were presented to subjects. The affective

reactions of the subjects on the dimensions of evaluation, potency and activity were recorded

and analyzed. The findings indicate that observers use different pieces of information in form-

ing impressions based on stimuli type and that what those pieces of information are varies by

affective dimension.

� 2002 Elsevier Science (USA). All rights reserved.

Keywords: Affect Control Theory; Visual stimulus; Written stimulus; Videotape

1. Introduction

It is not uncommon to hear the phrase, ‘‘I guess you had to be there.’’ But just

what is it about ‘‘being there’’ that makes social situations more understandable

to us? One answer proposed by some sociologists is that the visual information we

receive by witnessing something is richer and provides us with more cues about socialevents than mere words (verbal descriptions on paper).

The debate about the use of visual stimuli has been ongoing in sociology generally

and symbolic interactionism particularly for at least 25 years. Thompson (1978)

Social Science Research 32 (2003) 278–293

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E-mail address: [email protected].

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posited that visual imagery contained subtleties that can be difficult, if not impossi-

ble, to express using conventional linguistic approaches, i.e., writing. Thompson be-

lieved that sociologists� historical reliance on written data collection methods ignored

a rich amount of information that could only be communicated visually. He pro-

posed that sociologists ought to be utilizing media such as still photography and vid-eotape in data collection. 1

The idea that videotape could be especially useful has also been discussed. Couch

(1986) argued that videotape provided a multisensory record of social acts that pro-

vided a flow record for the act and its emergent complexity. Bastien and Hostager

(1993) continued this line of reasoning and developed a protocol that linked individ-

ual cognition with social processes recorded on videotape.

Despite this discussion and general agreement that visual stimuli ought to be

explored, very few studies have actually made verbal–visual comparisons. Thomp-son et al. (1974) contrasted the effect of written descriptions of the mass killings

at My-Lai to photographs of those events. Those subjects who observed the

photographs were more condemnatory of what occurred at My-Lai than were

those who read a written account. Females and those subjects with visual-type

hobbies were more strongly influenced by the photographic images. The authors

concluded that visual stimuli were more evocative for a highly emotional social

event.

The study described in this paper is the first examination of which I am aware thatexamines the cognitive and affective differences resulting from encountering the same

social events either in written format or visual (videotaped) format. Unlike the

Thompson, Clarke and Dinitz study, I will be examining a number of different social

situations that vary in their emotional intensity (but that are generally not very in-

tense). The current study relies on Affect Control Theory (ACT) to provide the struc-

ture by which I will measure the affective responses. I present a brief synopsis of that

theory before turning to the description of the study itself.

1.1. Affect Control Theory

Affect Control Theory is a symbolic interactionist theory that posits that indi-

viduals acting in social situations and witnesses to those situations attach cultural

meanings called fundamental sentiments to the elements of those social situations

(actors, behaviors, objects, settings, etc.). 2 This perspective is descended from the

pioneering work of Goffman (1959) and the Chicago school on impression forma-

tion. Goffman (1959) believed that individuals seek to acquire information ininteraction that will be helpful to their understanding. Affect Control Theory

follows that logic and quantifies the information received in interactional

situations.

1 Thompson in fact had an even broader agenda and suggested that visual techniques should be

employed not only in data collection, but in other research and teaching activities as well.2 See MacKinnon (1994) for a thorough description of the symbolic interactionism of Affect Control

Theory.

L. Slattery Rashotte / Social Science Research 32 (2003) 278–293 279

The process of defining situations involves locating appropriate roles or identities

for oneself and for other interactants at any given time and place and in any situation

(Heise, 1988). The labeling of identities for all actors in a situation, while not fixed

and unchanging, yields a definition of the current situation which is both fairly stable

and (when institutionally anchored) often consistent across actors and observers(Heise, 1988). Cultural rules tell us what realm of behaviors might be appropriate

for specific actors (persons performing behaviors) in each given situation.

In ACT, the definitions of actors and behaviors are quantified on three dimen-

sions: evaluation, potency, and activity (EPA), a widely recognized set of dimensions

and measurement operations first proposed by Osgood et al. (1975) and used exten-

sively in sociological research (e.g., Rashotte and Smith-Lovin, 1997; see Heise, 1988

for list). These dimensions capture cognitive and affective responses to external per-

sons, things, and actions. Evaluation measures sentiments of goodness versus bad-ness. Potency measures powerfulness versus powerlessness. Activity measures

liveliness versus passivity. Within a culture, identities and behaviors have highly con-

sensual fundamental EPA ratings. 3 ACT generally measures each dimension (E, P,

and A) on a scale from )4 to +4. For example, in the United States, ‘‘mother’’ is seen

as quite good (2.4), fairly powerful (1.4), and fairly active (1.3). ‘‘Provoke’’ has fun-

damental EPA ratings )1.2, 0.3, and 0.7. Thus, that action is seen as fairly bad, nei-

ther powerful nor weak and slightly active. Often, each dimension�s rating is

collapsed to either a positive or negative rating, thus producing eight affective pro-files (E+, P+, A+; E+, P+, A); E+, P), A+; E+, P), A); E), P+, A+; E), P+,

A); E), P), A+; and E), P), A)).

Events produce transient impressions for actors and observers that can temporar-

ily alter the EPA ratings for any part of the scenario: actor, behavior, and nonverbal

cue or object. In other words, events change people�s feelings about things (Smith-

Lovin, 1988). The fundamental sentiments generally associated with identities and

behaviors are altered through social events.

2. Materials and methods

For this study, I prepared two sets of stimuli in order to see if the stimuli type

would produce different meaning structures. One set was written and the other

was videotaped. The written set consisted of descriptions of the events in the video-

taped set. Each event was a complete situation including a subject identity, a behav-

ior, a nonverbal behavior, and an object identity.Completely crossing all of the variables would be impossible (8 actor profiles� 8

object profiles� 8 nonverbal behavior profiles� 8 behavior profiles¼ 4096 possible

3 These dimensions have since been shown to correspond to neurological activity and it has been

demonstrated that the capacity to think of things in these terms is universal (Chapman et al., 1980). In

1975, Osgood, May and Miron showed these dimensions to be universal in a cross-cultural study and

concluded that while some variations do exist across cultures and subcultures, the general findings are

robust.

280 L. Slattery Rashotte / Social Science Research 32 (2003) 278–293

events). Instead, I use a design that provides maximum variation on these variables

while limiting the actual number of events to a feasible number. Thus, I did not need

to create and study all possible combinations in order to explore the effects. The

event set has an 8 � 8 Graeco-Latin square. This design requires four independent

variables. All variables in the design must have the same number of levels for themaximization of variation to occur. For this study I have eight levels of each inde-

pendent variable—the eight combinations of three two-level factors—which is one

normal permutation of the design (Fisher and Yates, 1963). Evaluation, potency,

and activity are the three factors; a rating as positive or negative (on the )4 to +4

scale) created the two levels. As stated above, taken together the EPA ratings yield

eight configurations.

The particular identity or behavior used to fulfill each level of each variable draws

on past research on fundamental meanings. They were chosen because they fit theeight EPA configurations most strongly and because they were useful in describing

a large number of events. Heise�s (1979) appendix, which lists the ratings for hun-

dreds of identities and behaviors, was used to select the actor and object–person

identities and the behaviors for each profile. 4 The ratings obtained in Rashotte

(2001) were used to locate nonverbal behaviors fitting each profile. 5

An example of an event is ‘‘The lady wrinkles her nose and greets the warden.’’

There were a total of 64 events created this way. The full list of 64 events was split

into eight subsets which each contained eight events. 6

There are several implications of working with a small sample of only 64 events.

This is typical in exploratory work on impression formation processes; samples were

similarly small in the studies of Heise (1969, 1970), Smith-Lovin (1979), and Averett

and Heise (1988). However, the small number of cases does limit the consideration of

interaction effects. Still, in all previous studies major effects were reliably identified.

There is no reason to presume that such will not be the case here.

2.1. Additional procedures for videotape stimuli

For the videotape stimuli, student actors were recruited mainly from the Theater

Department at a large public university with the incentive of pay. Additional actors

were recruited from the Department of Sociology as needed. The actors were briefed

on the basics of the study and trained with regard to the nonverbal behaviors. This

was done using communication research and psychological studies on nonverbal

displays. In particular, a video produced by the University of California (Archer,

1993) was used to direct the training of the performers on the paralinguistic behav-iors and similar materials were used for physical nonverbal behaviors (e.g., Ekman,

1982).

4 For more detail on the collection of the out-of-context ratings, see Smith-Lovin (1988).5 These ratings were all collected via paper and pencil stimuli.6 Other examples of events include: ‘‘The buddy punches and mocks the wrongdoer;’’ ‘‘The assailant

speaks in a quavering voice and flatters the lady;’’ ‘‘The alcoholic blinks and contemplates the flirt;’’ and

‘‘The clerk leans back and appeases the aunt.’’ A complete list of all 64 events is available from the author.


Actors worked in pairs. Each actor performed in four events with each of two oth-

ers (one of the same gender and one of the other gender). Thus, each actor is in a

total of eight scenes. Subjects saw any given actor only once (see below for more de-

tail on the subjects). I randomly assigned actors to scenes within the constraint of

being in a given subject subset only once.Each actor was dressed in typical college student clothing. In other words, they

were not in costume, nor were they dressed in such a way as to convey high or

low status. The actors were all of average attractiveness, as rated by pretest subjects

(see below for more on the pretest). In addition, since actors were randomly assigned

to events across the dimensions of meaning, it is unlikely that characteristics of any

given actor would affect the mean ratings in any significant way.

I videotaped each scene of 15–40 s in the laboratory from 1 to 5 times, as needed,

to be sure that the actors were communicating clearly the proper identities and be-haviors, including vocal characteristics. Actors were instructed, as mentioned above,

especially with regard to the expressive, nonverbal behaviors.

The raw footage was then edited. The best take of each scene was isolated and

pared down to 15–20 s so that each event was portrayed with basically the same

amount of information. I then ordered the scenes as they were presented in the writ-

ten stimuli using the same subsets to maximize the comparability of the two studies.

I pretested the videotape stimuli on graduate subjects first to make sure that the

tapes are properly depicting the actor identities, behaviors, object–person identities,and the nonverbal behaviors. That is, I gave pretest subjects open-ended response

sheets and asked to determine the identity of the actor and object, the behavior being

performed and what nonverbal behavior accompanied it. In other words, they were

asked for a very specific definition of the situation from the visual stimulus. The vid-

eotapes were then altered in some slight ways—a few scenes were re-shot and a cou-

ple of scenes were re-edited—to fix some identification problems identified by this

pre-testing process.

The tapes were then further pre-tested, this time on undergraduate subjects. Thesepretests were done in a manner similar to the data collection described below and

found no problems that required altering of the tapes. Over 90% of the pretest sub-

jects could correctly identify the event elements. There was not a large amount of

variation in subjects� ability to identify actors, behaviors, object persons, or nonver-

bal cues.

2.2. Data collection

Students were recruited from undergraduate sociology courses and paid for their

participation ($5 for a written subset or $10 for a videotaped subset). No student

participated in both the written and videotaped stimuli conditions of the study.

The response sheet consisted of the standard 9-point scales for evaluation, potency,

and activity ()4 to +4). Each event element was rated on each dimension.

The written event subsets were presented to 1–4 students at a time. The students

were seated around a table in the laboratory and instructed not to look at one an-

other�s papers. The researcher was present at all times to ensure that participants


did not discuss their responses. About 20 subjects rated each written event subset, for

a total of 157 subjects.

The videotaped events were shown to groups of 5–10 subjects at one time. 7 They

were spaced out across the room and asked to keep silent. Each group saw a set of

eight events corresponding to a row in the Graeco-Latin square design. 8 Each grouptook about 25 min. Here, subsets ranged from 16 to 20 subjects, for a total of 132

subjects.

3. Results

Descriptive statistics for the EPA ratings for the written events are presented in

Table 1 and for the videotaped events in Table 2. 9 The means for each rating, forthe overall sample, for males and for females, hover around 0. That indicates that

the event elements presented to cover the full range of dimension space. The variabil-

ity, as measured by the SDs, is not noticeably different for males and females for either

type of event. What is noticeable, however, is the greater amount of variability present

in the ratings of event elements presented in the videotapes rather than in written

form. This can be seen both in the SDs and in the minimum/maximum ratings.

Regressions predicting the meanings of the behaviors, actors, and objects in con-

text were run. More specifically, the transient behavior, actor, and object ratingswere regressed on the fundamental sentiments for the event elements (actor, behav-

ior, nonverbal cue, and object). The results of these analyses are presented in Tables

3–11. Two sets of models are presented for each dimension of the transient rating

(E, P, and A): those that include fundamental sentiments for each element only

on the same dimension and those that include the sentiments for each element on

all dimensions.

3.1. Behavior

3.1.1. Evaluation

Table 3 presents the findings for predicting in-context evaluation ratings of the be-

haviors. For the written stimulus, in the simpler model (evaluation sentiments only),

7 Thus, the observations are not completely independent. All attempts were made to ensure that

subjects did not influence one another; the researcher was present in the room at all times, the subjects

were asked not to speak to one another and no one stimuli was presented to only one group. Of course

these procedures could not completely rule out any communication or contamination between

observations, but I believe those negative effects were minimized.8 The mixed design had subjects nested in levels of object profiles (rows) and crossed with levels of

actor profiles (columns). The variable in which to nest the subjects is of no substantive importance—actors

could have just as easily been chosen. As noted above, each actor and object person were different

performers in order to control for any possible carryover effects. I assume no statistical interaction

between subjects and the treatment effects.9 The descriptive statistics for each of the 128 events (64 written and 64 on videotape) are not presented

for the sake of space. These are available from the author upon request.


the behavior�s fundamental sentiment rating is the only one that has a significant im-

pact on the in-context transient rating. As would be expected, it has a positive effect.

When the other dimensions are included, the behavior�s fundamental activity rating

is also significant and has a negative effect. In addition, now the nonverbal cue�s eval-

uation and potency ratings are significant (positive effect and negative effect, respec-

tively).

For the visual stimulus, the findings for the simpler model are the same. The be-

havior�s fundamental evaluation rating has a significant, positive effect on the tran-sient behavior rating. In the full model, however, the behavior�s fundamental

Table 1

Descriptive statistics—written events

Mean SD Min Max N

Behavior Overall

E 0.274 0.584 )1.500 1.750 157

P 0.817 0.740 )0.875 3.563 156

A 0.639 0.714 )1.750 3.688 156

Males

E 0.320 0.565 )1.063 1.688 79

P 0.723 0.673 )0.750 2.623 78

A 0.641 0.642 )1.750 2.250 78

Females

E 0.228 .602 )1.500 1.750 78

P .910 .796 )0.875 3.563 78

A .636 .784 )1.063 3.688 78

Actor Overall

E 0.007 0.673 )1.375 2.063 155

P 0.564 0.766 )1.438 2.750 148

A 0.676 0.731 )0.875 3.000 153

Males

E 0.055 0.670 )1.250 2.063 77

P 0.568 0.766 )1.313 2.750 75

A 0.746 0.736 )0.875 2.563 76

Females

E )0.040 0.678 )1.375 2.000 78

P 0.560 0.771 )1.438 2.688 73

A 0.606 0.724 )0.625 3.000 77

Object Overall

E )0.049 0.642 )1.875 2.500 157

P )0.511 0.635 )2.750 1.438 152

A )0.394 0.667 )2.438 1.813 155

Males

E )0.147 0.546 )1.250 1.250 79

P )0.555 0.623 )2.125 1.438 77

A )0.442 0.673 )1.938 1.813 78

Females

E 0.050 0.717 )1.875 2.500 78

P )0.465 0.649 )2.750 1.375 75

A )0.345 0.663 )2.438 1.438 77


evaluation rating is not significant. The behavior�s activity rating does now show a

significant negative effect.

3.1.2. Potency

The models predicting in-context potency ratings of the behaviors are presented in

Table 4. For the written stimulus, only the behavior�s transient potency rating is sig-

nificant in predicting the in-context rating in the simpler model. It has a positive ef-

fect. In the full model, this effect remains. Also in the full model, the nonverbal cue�sevaluation rating has a significant, positive effect.

Table 2

Descriptive statistics—videotaped events

Mean SD Min Max N

Behavior Overall

E )0.002 1.143 )3.875 3.375 132

P 0.561 1.140 )3.875 3.625 132

A 0.468 1.141 )3.875 2.625 132

Males

E 0.104 1.383 )3.875 3.375 48

P 0.492 1.175 )3.875 2.625 48

A 0.487 1.150 )3.875 2.625 48

Females

E )0.063 0.984 )2.875 2.375 84

P 0.600 1.125 )2.750 3.625 84

A 0.457 1.142 )3.625 2.625 84

Actor Overall

E )0.250 1.033 )3.000 2.75 134

P 0.549 1.084 )3.000 3.000 131

A 0.371 1.081 )3.750 2.875 132

Males

E )0.161 1.027 )3.000 2.750 48

P 0.497 1.023 )3.000 3.000 47

A 0.471 0.997 )3.000 2.500 48

Females

E )0.300 1.040 )2.625 2.500 86

P 0.577 1.121 )2.500 2.875 84

A 0.314 1.129 )3.750 2.875 84

Object Overall

E 0.058 1.072 )4.000 3.000 134

P )0.094 0.934 )4.000 1.750 132

A )0.112 1.028 )4.000 1.875 131

Males

E 0.013 1.190 )4.000 2.500 48

P )0.165 0.980 )4.000 1.375 47

A )0.114 1.082 )4.000 1.625 47

Females

E 0.083 1.007 )2.125 3.000 86

P )0.054 0.911 )2.000 1.750 85

A )0.110 1.003 )3.750 1.875 84


For the visual stimulus, no elements were significant in predicting in-context be-

havior potency when only potency ratings were included. In the full model, with all

dimensions, only two elements had a significant effect. The nonverbal behavior�s ac-

tivity level had a positive consequence and the object�s activity level had a negative

consequence.

3.1.3. Activity

Table 5 shows the regressions for the in-context activity rating of the behavior.Consistent with results described above, in the written study, the only element

to have a significant effect in the simpler model was behavior activity. Its effect is

Table 3

Regression coefficients for predicting in-context behavior evaluation, N¼ 64

Written—Model 1 Written—Model 2 Video—Model 1 Video—Model 2

Intercept )0.064 0.179 )0.104 0.133

Actor E 0.061 0.163 0.132 0.156

Object E 0.013 )0.131 )0.062 )0.088

Nonverbal E 0.136 0.251� 0.106 0.139

Behavior E 0.648� 0.464� 0.297� 0.173

Actor P 0.102 0.067

Object P )0.204 )0.063

Nonverbal P )0.414� )0.123

Behavior P 0.369 0.289

Actor A )0.081 )0.019

Object A )0.053 )0.117

Nonverbal A 0.047 0.000

Behavior A )0.593� )0.491�

R2 .4841 .6403 .2488 .3760

* p < :05.

Table 4

Regression coefficients for predicting in-context behavior potency, N¼ 64


Intercept 0.619 0.690 0.501 0.562

Actor E 0.120 0.012

Object E 0.040 )0.007

Nonverbal E 0.111� 0.103

Behavior E )0.105 )0.113

Actor P 0.062 0.069 0.006 0.040

Object P )0.062 )0.097 0.066 0.019

Nonverbal P 0.085 )0.002 0.152 0.012

Behavior P 0.401� 0.475� 0.158 0.189

Actor A )0.052 0.046

Object A )0.138 )0.237�

Nonverbal A 0.087 0.171�

Behavior A 0.000 0.125

R2 .2464 .3814 .1072 .3582

* p < :05.


positive. In the full model, this is still a significant effect. In addition, the behavior�sfundamental evaluation rating has a negative effect.

For the visual study, in the simple model, only behavior activity has a significant

effect, and it is positive. In the full model, this effect still holds.

3.2. Actor

3.2.1. Evaluation

As seen in Table 6, three elements predict the actor�s in-context evaluation ratingin the simple written model: actor evaluation, nonverbal evaluation, and behavior

Table 5

Regression coefficients for predicting in-context behavior activity, N¼ 64


Intercept 0.378 0.414 0.362 0.417

Actor E 0.109 0.150

Object E )0.026 )0.008

Nonverbal E 0.097 0.080

Behavior E )0.135� )0.025

Actor P 0.011 )0.007

Object P )0.059 0.026

Nonverbal P )0.083 )0.005

Behavior P )0.173 )0.169

Actor A 0.025 )0.021 0.008 )0.061

Object A )0.122 )0.140 )0.047 )0.054

Nonverbal A 0.032 0.072 0.133 0.148

Behavior A 0.655� 0.621� 0.406� 0.415�

R2 .4827 .5950 .2321 .3349

* p < :05.

Table 6

Regression coefficients for predicting in-context actor evaluation, N¼ 64


Intercept )0.470 )0.298 )0.296 0.021

Actor E 0.361� 0.386� 0.311� 0.340�

Object E )0.039 )0.123 )0.167 )0.141

Nonverbal E 0.242� 0.311� 0.080 0.089

Behavior E 0.358� 0.305� 0.230� 0.195

Actor P 0.154 0.144

Object P )0.183 )0.047

Nonverbal P )0.180 0.049

Behavior P )0.097 0.045

Actor A )0.035 )0.142

Object A )0.039 )0.161


Behavior A )0.239 )0.236

R2 .4692 .5479 .2978 .3465

* p < :05.


evaluation (all positive effects). These three effects are all present in the full model as

well. For the videotaped events, actor evaluation and behavior evaluation have po-

sitive effects in the simple model, but only actor evaluation remains in the full model.

It is striking that nonverbal behavior evaluation is more important in the written

study than in the video study.

3.2.2. Potency

Table 7 shows the results for predictions of in-context actor potency. For the writ-

ten study, nonverbal potency is predictive in the simple model and the full model.

Nothing else has a significant impact. In the video study, nonverbal potency also

has a positive effect in the simple model. However, in the full model, this effect is

not present. The object–person�s fundamental activity rating does now have a nega-

tive effect.

3.2.3. Activity

The regressions predicting in-context actor activity ratings are presented in Table

8. Actor activity, nonverbal activity and behavior activity all have positive effects

in the simple written and full written models. In the full model, the nonverbal

behavior�s fundamental potency rating also has a positive effect. For the videotape

study, no variables are significant in either model.

3.3. Object–person

3.3.1. Evaluation

The models predicting in-context object–person ratings for evaluation are shown

in Table 9. In both the simple and full models for the written study, the object�s fun-

damental evaluation rating has a significant, positive effect, as expected. In addition,

in each of those models the actor�s evaluation rating has a negative effect. In the

Table 7

Regression coefficients for predicting in-context actor potency, N¼ 64


Intercept 0.200 0.042 0.425 0.650

Actor E 0.131 0.051

Object E 0.056 0.107

Nonverbal E 0.027 0.076

Behavior E )0.038 )0.185

Actor P 0.184 0.125 0.052 0.111

Object P )0.018 )0.032 )0.082 )0.133

Nonverbal P 0.435� 0.371� 0.408� 0.308

Behavior P 0.216 0.290 )0.050 0.028

Actor A 0.231 )0.038

Object A )0.194 )0.375�


Behavior A )0.011 0.176

R2 .3108 .4962 .1410 .3319

* p < :05.


video study, the actor�s evaluation rating continues to have this negative effect inboth models and the object�s evaluation rating continues to have a positive effect.

In both of the video models, additionally, the nonverbal behavior�s evaluation rating

has a positive effect.

3.3.2. Potency

As seen in Table 10, the only significant variable predicting in-context object po-

tency ratings for the simple model of the written study is actor�s potency, which has a

positive effect. In the full model of the written study, however, object potency andobject activity have positive effects and nonverbal evaluation has a negative effect.

Table 9

Regression coefficients for predicting in-context object evaluation, N¼ 64


Intercept )0.279 )0.467 )0.029 0.070

Actor E )0.219� )0.224� )0.259� )0.277�

Object E 0.711� 0.676� 0.498� 0.531�

Nonverbal E 0.065 0.041 0.145� 0.168�

Behavior E 0.033 )0.020 0.005 )0.035

Actor P 0.025 0.091

Object P 0.144 0.014

Nonverbal P )0.012 )0.164


Actor A 0.003 )0.002

Object A 0.147 )0.166

Nonverbal A )0.015 0.051

Behavior A )0.052 0.092

R2 .6682 .7267 .5286 .5825

* p < :05.

Table 8

Regression coefficients for predicting in-context actor activity, N¼ 64


Intercept )0.023 )0.083 0.263 0.166

Actor E )0.002 0.123

Object E 0.072 )0.007

Nonverbal E )0.142� )0.021

Behavior E 0.003 )0.170

Actor P )0.020 0.060

Object P 0.032 )0.100

Nonverbal P 0.370� 0.290


Actor A 0.334� 0.342� 0.062 0.002

Object A )0.006 )0.033 )0.132 )0.140

Nonverbal A 0.315� 0.217� 0.146 0.077

Behavior A 0.363� 0.276� 0.305 0.194

R2 .4615 .6161 .0977 .2289

* p < :05.


No variables have significant effects in the simple model of the videotape study. For

the full model, only the object�s fundamental activity rating is significant and its ef-

fect is positive, as with the written study.

3.3.3. Activity

Table 11 shows the regression predicting in-context object–person activity ratings.

The object�s fundamental activity rating has a positive effect in both written models.

In the full model, the behavior evaluation rating also has a positive effect. Object ac-

tivity is also predictive in the simple model for the video study. However, it is not in

the full model. In fact, no variables have a significant effect in the full model.

Table 11

Regression coefficients for predicting in-context object activity, N¼ 64


Intercept )0.645 )0.616 )0.323 )0.284

Actor E 0.056 )0.051

Object E )0.141 0.020

Nonverbal E )0.020 )0.143

Behavior E 0.186� 0.151

Actor P 0.011 0.149

Object P 0.039 0.030

Nonverbal P )0.115 0.128

Behavior P )0.197 )0.114

Actor A 0.059 0.002 )0.046 )0.136

Object A 0.194� 0.306� 0.336� 0.340

Nonverbal A )0.100 )0.074 )0.045 )0.093

Behavior A )0.036 0.068 )0.024 )0.017

R2 .1052 .4103 .0870 .2273

* p < :05.

Table 10

Regression coefficients for predicting in-context object potency, N¼ 64


Intercept )0.440 )0.835 )0.025 )0.278

Actor E )0.027 0.106

Object E 0.037 )0.004

Nonverbal E )0.174� )0.141

Behavior E 0.111 0.125

Actor P 0.225� 0.142 0.158 0.077

Object P 0.119 0.212� 0.000 0.071

Nonverbal P )0.134 )0.029 )0.237 )0.112

Behavior P )0.038 )0.154 0.025 )0.023

Actor A 0.154 )0.043

Object A 0.302� 0.369�

Nonverbal A )0.052 )0.066

Behavior A 0.228 )0.020

R2 .1673 .4081 .0860 .2845

* p < :05.


3.4. Overall fit of the models

Consistently lower R2 were found in the videotaped study. In fact, for every

dependent variable, the written models were more predictive than the videotape

models. I believe this is due to two factors. First, the increased variability in thein-context ratings (noted above) could have made them harder to predict. Second,

and more importantly, there was much more information presented in the videotapes

that could be introducing variability in the in-context rating process. In effect, this

information may be introducing identity modifiers or other definition of situation is-

sues that were not explicitly measured in this study. Clearly, more information is be-

ing processed, probably in a more complicated way, in interpreting and defining the

events witnessed on videotape.

4. Discussion and conclusions

I will now summarize the differences found between the videotape study and the

written study. I will examine each affective dimension in turn, ending with some sum-

marizing thoughts. I will focus on the full models, since in every case they are more

predictive.

Turning to the results regarding in-context evaluation ratings, we find that thevideotape stimulus actually found a simpler picture for behaviors and actors than

the written stimulus did. 10 It may be that the goodness of behaviors and actors is

clearer in the videotapes and that observers do not need to use as much other infor-

mation as readers do to get impressions of this. For object–persons, however, view-

ers use the same information as readers to determine evaluation, with the additional

of the evaluation rating of the nonverbal behavior. The visual cue of a good nonver-

bal behavior has more impact than the written description of it.

Again with potency, we see that the videotape models have fewer significant vari-ables for predicting in-context behavior and object ratings. Interestingly, fundamen-

tal potency ratings tend to be important in prediction for the written models, but

activity ratings are more likely to have an effect in the videotape models. Both in-

context actor potency ratings and in-context object–person potency ratings go down

if the object–person activity rating is high.

Yet again, in predicting activity, we see that the videotape models have fewer sig-

nificant effects. In fact, there were no significant variables in predicting in-context ac-

tivity ratings for actors or objects for the video study. Additionally, only one, thebehavior�s fundamental activity rating, was significant in predicting the behavior�sin-context behavior rating, and that is not an interesting finding.

Overall, it does appear that different pieces of information are significant in cre-

ating all dimensions of the transient behavior ratings depending on the nature of

10 Of course, one reason for this finding may be that the variables in the videotape models are

interacting statistically. However, as mentioned earlier, the small sample size limited consideration of

interactions.


the stimulus. These results are consistent with the idea that visual stimuli provide us

with more information, and therefore a richer picture, of social events. It may be for

this reason that the elements used to measure information do not help us to under-

stand situations defined via visual stimuli as well as those defined via written stimuli.

However, when the product-moment coefficients are calculated for the regression

coefficients in the full models (see Table 12), we see that overall the patterns are more

similar than the examination of significant coefficients might indicate. The relative

contributions of the event components in predicting evaluations are very similarfor the verbal and visual stimuli. The relative contributions of the event components

in predicting the other dimensions are moderately similar for the two stimuli types,

with one exception. In predicting the activity rating of the behavior, the patterns

for the visual and written stimuli are almost identical, as indicated by the coefficient

of 0.94.

Just exactly what the differences in the pictures are—and which is more accu-

rate—still needs to be determined. Much more research is needed to more clearly de-

termine how the processes of impression formation differ for various types of stimuli.

Acknowledgments

Thanks to Lynn Smith-Lovin, Linda Molm, Miller McPherson, Calvin Morrill,

Murray Webster, Kevin D. Childers, and the reviewers at SSR for their contribu-

tions to this work. This research was supported by the Graduate College, University

of Arizona and NSF Grant SBR-9701587 to Lynn Smith-Lovin and the author.

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Table 12

Product-moment correlations between full model regression coefficients

Impression of: On evaluation dimension On potency dimension On activity dimension

Actor 0.81 0.70 0.62

Behavior 0.93 0.69 0.94

Object 0.81 0.66 0.64


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