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).
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.
