The Personality of Terms and Concepts Used in Online Material

A. Dawn Shaikh, Barbara S. Chaparro, & Doug Fox

Summary. This article presents results from a study investigating the personality of terms and concepts used in online content. Participants were asked to rate 120 terms or career names on three factors (Potency, Evaluative, and Activity, based on Osgood, 1957). Potency refers to the strength of the term, Evaluative refers to the goodness or beauty of the term, and Activity refers to the level of activity or speed of the term. Results are quantified by term and by career name. For example, a term that is high on the Potency factor was found to be "power tools", high on the Evaluative factor was "perfume", and high on the Activity factor was a "mountain bike". Interface designers will find these results helpful when trying to insure congruency between online content and user interface design elements and style (i.e., typography, layout aesthetics).

Introduction

Designers creating online material often are faced with the difficulty of matching the "personality" of their online content to their design (layout, typeface, etc.). Likewise, researchers studying the perceived personality of online material are faced with the difficulty of separating the influence of the online content from the user interface design. Research has shown that the congruency of the design to the content is important in overall user perceptions. For example, Doyle and Bottomley (2004) investigated the role of typeface in product selection and showed that a product with a congruent font (one that was judged to have the same characteristics as the product) was more likely to be chosen for further investigation and for purchase than one that was presented in an incongruent font. They also found that typeface had a powerful effect even with meaningful brand names, which suggests that choosing a typeface could influence profit potential.

In repeated tests of semantic differential scales (SDS), Osgood, Suci, and Tannenbaum (1957) found three factors to explain the meaning of various stimuli; these factors were named Potency, Evaluative, and Activity. The Potency factor indicates the strength or power of items being judged (such as strong/weak). The Evaluative factor measures the assessment of items (such as good/bad, beautiful/ugly). The Activity factor implies the activity level of the items (such as active/passive, fast/slow).

Determining the loadings for particular online content or simple terms and concepts on each factor provides insight to the persona of that information. This can be used in design to ensure congruency in a user interface, such as between a company logo and its corresponding website content.

The purpose of this study was to determine the personality factor loadings of many terms and concepts used in online materials available today. This study was a necessary precursor to other research by the authors to evaluate the personality of typefaces used in a variety of online documents (e.g., resume, advertisement, website). The website ads and resumes being evaluated needed to be "framed" with content. Thus, the persona of the content first needed to be established.

Method

Online content terms were evaluated using semantic differential scales (SDS) to determine loadings on the three factors of Evaluative, Potency, and Activity. The terms were related to those that could be used for an online ad or a resume. For example, an ad for a hammer should have a different persona then an ad for perfume. Similarly, a resume for a florist should have a different persona than a resume for a webmaster.

A survey was conducted to choose the content for the website ads and the onscreen resumes. A list of terms and concepts was obtained through personal communication with J.R. Doyle. Doyle and Bottomley (2006) pre-tested over 100 items on the semantic factors of Potency, Evaluative, and Activity using a clustered anchor approach. The list of terms was rank ordered, and 55 terms representing the high, middle, and low point of each factor were selected for further testing. In addition to being representative of varying points on each factor, terms were selected only if they were exclusive to the factor. The original list was in British-English, so all terms were converted to American-English where necessary. An additional list of 65 career names from the US Department of Labor was added to the terms selected from Doyle and Bottomley list. The final list tested consisted of 120 terms and careers (69 careers and 51 terms).

The list of 120 terms was randomly broken down to 4 sets of 30 terms. The participants were asked to quickly rate each term on three scales (a modified version of the factors suggested by Osgood and associates 1957); they could also skip the item if they did not know its meaning by checking the appropriate box. This methodology (as shown in Figure 1) was recommended by Doyle and Bottomley (2006) as an efficient method to quickly determine semantic qualities of terms.

Figure 1. Example of how the terms were presented (in order of Potency, Evaluative, and Activity factors, respectively).

Figure 1. Example of how the terms were presented (in order of Potency, Evaluative, and Activity factors, respectively).

Participants were recruited through undergraduate psychology classes on the local university campus and spent approximately 10 minutes completing the consent form and survey. A total of 120 participants completed the surveys (N of 30 per set of terms). Data from four participants was eliminated due to incomplete surveys. Ten individual scores were identified across the remaining 116 participants as outliers and were replaced with the mean score (Tabachnick and Fidell, 2001). The career "actuary" was a familiar term to only six participants and was removed from further analyses.

Results

Results are listed in Table 2 and 3. Loadings for the three factors and corresponding rank are given for each of the 119 terms evaluated. For example, the term "dancer" had the highest loading for the factor of evaluative, suggesting that it is high on goodness and beauty. The term "fast food" was ranked the lowest on this factor. The highest and lowest ranks for careers are shown in Table 4 and for general terms/concepts in Table 5.

Table 1. Loadings and rankings of the three factors for the CAREERS evaluated.

Term Score
Potency
Score
Evaluative
Score
Activity
Rank
Potency
Rank
Evaluative
Rank
Activity
accountant 0.889 -0.074 -1.444 46 85 101
actor 0.000 1.955 1.704 72 11 8
agricultural and food scientist 0.615 -0.231 -1.077 55 93 85
architect 0.000 1.483 0.276 71 22 42
artist -1.370 1.630 0.037 97 18 49
automotive mechanic 2.483 -0.517 0.069 8 102 47
bookkeeping clerk -1.333 -0.889 -2.259 96 110 118
butcher 2.517 -1.483 -0.310 7 114 59
carpenter 2.568 0.207 0.862 6 76 23
chemist 0.630 0.370 -0.926 54 68 77
childcare worker -1.444 0.704 0.815 100 50 25
civil engineer 1.500 -0.167 -1.333 29 91 95
coach 1.296 0.037 1.704 34 81 7
computer hardware engineer 1.759 0.517 -0.793 24 60 71
computer software engineer 0.885 0.385 -0.962 47 67 79
computer support specialist 0.885 -0.192 -1.423 47 92 98
cost estimator 0.917 -0.042 -1.458 43 84 103
court reporter -1.185 0.000 -0.926 90 83 74
dancer -2.519 2.417 1.593 115 1 10
database administrator 0.731 0.154 -1.192 50 77 91
designer -1.852 2.370 1.185 105 3 17
desktop publisher 0.143 0.679 -1.286 67 51 93
disc jockey 1.286 0.250 2.250 35 73 2
doctor 0.074 1.926 -0.037 70 12 52
drafter 0.909 -0.091 -0.727 44 86 69
economist 0.667 0.333 -1.185 53 70 90
electrical engineer 1.250 0.517 -0.724 36 61 68
electrician 2.148 0.037 0.259 16 80 44
engineering technician 1.586 0.414 -0.931 27 65 78
environmental scientist 0.731 -0.115 -1.038 50 88 81
farmer 2.103 -0.276 -0.621 18 94 66
financial analyst 0.464 0.143 -1.607 59 78 107
fire fighter 2.765 0.926 2.370 2 40 1
florist -2.519 2.185 -0.704 115 5 67
hairdresser -1.931 1.586 0.655 107 20 33
human resources assistant -0.926 0.556 -0.407 86 55 62
judge 1.759 0.586 -0.310 25 54 58
landscape architect 0.407 1.704 0.185 62 17 45
lawyer 1.379 0.897 1.103 31 41 18
librarian -1.414 -0.103 -2.448 98 87 119
loan officer 0.556 -0.444 -1.741 56 98 112
musician -0.552 1.276 0.793 83 30 27
nurse -1.724 0.897 0.724 102 41 30
paralegal -0.038 0.538 -0.577 73 56 65
pest control 2.000 -1.778 -1.444 20 117 101
pharmacist -0.185 1.037 -0.926 77 36 74
photographer -0.704 1.593 0.185 85 19 45
physicist 1.111 0.778 -0.556 39 48 64
pilot 1.379 1.276 0.897 31 31 22
police officer 2.138 0.143 1.517 17 79 13
politician 1.519 -0.333 0.333 28 95 40
professional athlete 2.172 1.483 2.207 14 23 4
psychologist -0.185 1.481 -0.111 78 24 56
real estate agent 0.179 0.679 0.929 66 52 21
recreation & fitness worker 0.929 1.393 1.536 41 28 11
recreational therapist -0.167 0.958 0.375 76 39 37
reporter 0.074 0.259 1.407 69 72 15
secretary -2.000 0.815 -0.852 109 46 73
social worker -1.310 0.241 -0.034 95 75 51
statistician 0.926 -0.148 -1.852 42 89 115
surveyor 0.815 -0.519 -1.444 49 103 100
systems analyst -0.077 0.000 -1.692 75 82 110
teacher -1.192 0.846 0.346 93 45 39
urban planner 0.273 0.409 0.727 63 66 29
veterinarian 0.250 1.357 0.357 64 29 38
webmaster 0.536 0.250 -1.179 57 73 89
writer -0.407 0.593 -1.111 82 53 87
zoo keeper 0.889 -0.407 0.963 45 97 20

Table 2. Loadings and ranking of the three factors for the TERMS evaluated.

Term Score
Potency
Score
Evaluative
Score
Activity
Rank
Potency
Rank
Evaluative
Rank
Activity
aspirin -0.370 -0.481 -1.222 81 101 92
bank or savings & loan 0.444 0.519 -1.630 61 58 108
bathroom towels -1.828 1.414 -1.172 104 27 88
book shop -1.034 0.862 -1.793 88 43 114
boxing gloves 2.207 -0.552 1.690 13 104 9
bricks 2.481 -0.741 -1.704 9 108 111
burglar alarm 1.667 0.444 2.074 26 64 5
cakes -2.444 2.000 -0.333 114 9 60
car tires 2.069 0.276 0.586 19 71 36
carpet -0.963 0.741 -1.444 87 49 99
chocolates -1.793 1.995 0.034 103 10 50
cigarettes 1.138 -2.172 -1.345 38 118 96
computer games 1.370 0.519 1.481 33 58 14
concrete 2.692 -1.500 -1.500 3 115 104
cooking oil -0.556 -0.556 -0.370 84 106 61
dating agency -1.069 -0.345 0.828 89 96 24
detergent (bleach) -0.276 -0.552 -1.069 80 105 83
fabric softener -2.685 0.778 -1.556 119 47 106
fast food 0.481 -2.407 -0.444 58 119 63
fountain pens -0.071 0.464 -1.107 74 62 86
garden furniture -1.185 1.037 -1.333 91 35 94
green house -1.185 1.222 -1.407 91 32 97
greeting cards -1.966 1.172 -0.793 108 33 72
hammer 2.571 -1.393 0.643 5 112 34
helmet 1.963 -0.444 1.519 21 98 12
ice cream -1.429 1.429 0.607 99 25 35
ice rink -0.250 1.829 0.321 79 14 41
insulation 1.000 -0.840 -2.000 40 109 117
knives (kitchen) 1.926 0.333 0.259 22 69 43
life insurance 0.679 1.000 -1.750 52 38 113
lipstick -2.655 1.862 -0.103 118 13 55
luggage 0.464 0.536 -1.000 59 57 80
mobile phones 0.103 1.552 1.000 68 21 19
mountain bike 2.407 2.074 2.222 12 7 3
perfume -2.379 2.414 -0.069 112 2 53
power tools 2.889 0.852 2.074 1 44 5
safe/vault 2.172 1.034 -1.069 14 37 82
semi truck 2.679 -0.679 0.679 4 107 31
shampoo -1.630 1.111 -0.741 101 34 70
soda/pop drinks 0.235 -0.148 0.741 65 90 28
sofa -2.380 2.147 -1.963 113 6 116
soft furnishings -2.103 2.069 -1.536 111 8 105
specialty jams -2.042 1.417 -0.125 110 26 57
sports watch 1.821 0.464 0.679 23 63 32
storage service 1.480 -1.440 -1.640 30 113 109
theatre -1.276 1.759 1.207 94 16 16
used cars 1.185 -1.593 -0.926 37 116 76
valentines cards -2.630 2.259 0.037 117 4 48
whisky 2.481 -0.481 0.815 9 100 26
wine -1.888 1.759 -0.071 106 15 54
work boots 2.439 -1.000 -1.071 11 111 84

Table 3. Summary of highest and lowest CAREERS by factor

  Potency Evaluative Activity
Highest Fire fighter
Carpenter
Butcher
Dancer
Designer
Florist
Fire fighter
Disc jockey
Pro athlete
Lowest Florist
Dancer
Secretary
Pest Control
Butcher
Bookkeeping clerk
Librarian
Bookkeeping clerk
Statistician

Table 4. Summary of highest and lowest TERMS by factor

  Potency Evaluative Activity
Highest Power Tools
Concrete
Hammer
Perfume
Valentine card
Sofa
Mountain bike
Power Tools
Burglar alarm
Lowest Fabric Softener
Lipstick
Valentine card
Fast Food
Cigarettes
Used cars
Insulation
Sofa
Book shop

Discussion

Results of this study are useful because they provide designers with quantitative data for content persona. Practitioners may use this data to choose appropriate content for online documents or ads. If the career content of a resume, for example, is considered evaluative (e.g., designer or dancer), then the design of the resume (e.g., typeface selection) should also be evaluative to provide a non-conflicting overall persona. Consistency between the design and content is important so that the appropriate message is conveyed and the author is perceived in a positive manner.

References

Doyle, J. R., & Bottomley, P. A. (2004). Font appropriateness and brand choice. Journal of Business Research, 57, 873-880.

Doyle, J. R., & Bottomley, P. A. (2006). Dressed for the occasion: Font-product congruity in the perception of logotype. Journal of Consumer Psychology, 16(2), 112-123.

Osgood, C. E., Suci, G. J., & Tannenbaum, P. H. (1957). The measurement of meaning. Urbana, IL: University of Illinois Press.

Tabachnick, B. G., & Fidell, L. S. (2001). Using multivariate statistics (4th ed.). Boston: Allyn and Bacon.

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