SELF PRESENTATION IN PERSONAL ADVERTISEMENTS:
A SOCIO-ECONOMIC ANALYSIS
ABSTRACT
A study was conducted on the content of personal
advertisements using data from 259 placements in a national
English newspaper. The data were first analysed by simple
comparison of the raw means for the variables. We then subjected
the male and female samples to separate data reduction, using
factor analysis, which confirmed the existence of differences
in male and female advertising strategies. The contribution of
'buying beauty' in the male analysis is weak compared to the
reciprocal offer, in the female analysis. Our analysis uncovers
a number of distinct male and female archetypes with differing
advertising strategies.
S.Cameron,University of Bradford, and A.Collins, University of
Portsmouth
I. Research on Mating Behavior
In sociobiological models (Barash,1979;Dawkins,1978;
Wilson,1975; Kenrick & Trost,1989), males are expected to display
lower levels of commitment in wanting to mate with a higher
number of partners, without reciprocal levels of investment in
the liaison. Males are expected to pursue this strategy by
offering resources which could support investment in children
whilst women offer physical attributes to enhance the 'quality'
of investment in children.
Relationships may have other 'consumption oriented'
dimensions independently of the genetic imperative (see
Becker,1973). Individuals may benefit economically from sharing
goods (such as housing) and non-sexual satisfaction may be
provided by sharing various activities with another. Admittedly,
some joint consumption activities may also be a mechanism for
exploring the suitability of prospective partners as parents.
Nevertheless an emphasis on these features indicates a lesser
intention for family centredness in the near future.
II.
In the personal ads. literature, the words used in the
adverts are coded into groupings in order that measures of what
is being offered and sought can be developed. Surprisingly, no
analysis has been offered of the patterning of offers and
requests within an advert. One would expect some degree of
intercorrelation between, and within, offers and request of
attributes, as there should be distinct profiles for types of
person; for example someone who emphasizes caring and home
centredness might be less inclined to emphasize physical
appearance whilst someone who emphasizes their own wealth might
be more inclined to seek physical attractiveness from their would
be partner. There are a myriad of possibilities for such
combining of items in the data. In the absence of strong
hypotheses about specific item combinations this paper adopts an
exploratory multivariate approach. Factor analysis is deployed in
order to suggest patterns of item combination within a set of
variables coded along the lines of the previous research.
Obviously, it makes sense to try to discern any such
patterns separately for males and females given the focus of the
literature on strategic, biologically grounded, gender
differences in dating behaviour. An analysis of such patterns
should provide much stronger evidence, than hitherto, with
respect to the models of dating behaviour proposed in the
literature.
III.
The data are taken from 259 personal advertisements
published in the 'Sunday Times' in August-October 1994. Whilst
there are many sources of such data, this particular publication
has the advantage of providing lengthy descriptions. There is no
limit to the length of advertisment other than the willingness to
pay of the placer. Increasingly, other similar publications in
the United Kingdom are tending to provide free, or low-cost,
advertisements of only 20-30 words maximum with a premium
telepone line reply service. Such advertisements give a very
limited indication of preferences and offers, as the advertiser
will put most of their effort into screening out the applicant
through appraising their telephone messages.
Measures and definitions are as follows. Scales for
description of own physical attributes (0-5 scale) and
description of physical attributes sought (0-5 scale). These
were constructed by noting the departures from a comprehensive
description checklist. For own physical attributes a 5 was
given for advertisements featuring over 80 % of checklist
categories (height,weight,physique,hair color etc; a 4 for 60-79
% and so on down to 0 for no such words, The other variables are:
the amount spent on the advert (in œ), seeks ambiguous
relationship, seeks casual relationship, seeks long-term
relationship, seeks platonic relationship, declared age,
declares divorced, declares single, declares children,
stipulates expensive leisure interests, seeks partner with
expensive leisure interests, offers finance, seeks finance from
partner, seeks partner with similar interests, stipulates
'sophisticated' leisure interests, seeks partner with
'sophisticated' leisure interests, stipulates sporting interests,
seeks partner with sporting interests. To facilitate the
presentation of the results memonics are used, as shown in Table
1, to represent these variables.
Financial characteristics offered and sought are used to
create categorical variables based on the appearance of key
phrases e.g. "wealthy gent seeks ...". For the 'expensive' tastes
variables keywords such as 'yachting' were used to code as 1. For
sophisticated tastes, items such as art,theatre were used to code
as 1. The classification into casual, long-term,platonic and
ambiguous groups was based on the presence of keywords. Inclusion
in the casual group was based on explicit reference to a
primarily sexual partner but also includes such phrases as
'holiday partner sought'; which have sexual overtones. Inclusion
in the long-term group is based on an explicit stipulation of
this or a stated desire for sexual exclusivity. Those classified
in the platonic group requested explicitly, or implicitly,
friendship without sex. Construction of the other variables ran
along similar lines.
Obviously, there is an element of imprecision in coding the
qualitative verbal data into quantitative information. We have
mainly tried to follow the existing literature but have
introduced a range of additional descriptors of preferences that
have not hitherto been considered. Advertisements were coded
independently by one author (A.C.) and another individual , and
then consensus was arrived at.
The data were first analyzed by simple comparison of the
raw means for the variables. We then subjected the male and
female samples to separate data reduction using principal
components (details not reported). To further crystallize the
strategy profiles, we subjected the leading components to
rotation, using the Quartimax criterion, to give us a factor
analysis.
IV. Results
Let us look first at the single variable comparisons in
Table 1. Men are more prone to offer financial support and seek
physical characteristics whilst women show the reverse pattern.
Men are also more prone to stipulate casual relationships and
spend more on their advertisements.
The full results of the factor analyses are shown in Tables
2-5. We follow the conventional practice of attaching labels to
the factors on the grounds of which variables exhibit
contemporaneously high loadings (over 0.5, in absolute terms,
as a rough rule of thumb). The labels are shown in Table 6.
The factor analysis shows that distinct groupings within the
advertisers can be detected. The type of rotation used here
imposes strict orthogonality on the final rotated factors. This
might be deemed to be a limitation if many individuals are wont
to advertise along more than one of the dimensions isolated here.
To take account of this, we also performed some oblimin rotations
which do allow correlation between the factors. However this
yielded a final set of factors which were very weakly correlated
with each other, even allowing for this feature to be at a
maximum. This suggests that there are very sharp cleavages across
the strategy profiles chosen by advertisers.
Names were assigned to the factors as shown in Table 6.
Eight factors were retained for rotation in the male analysis and
seven in the female. All 15 factors are named although many of
the later ones are based solely on a high coefficient for a single
variable. The naming is based on a degree of caricature of the
original word stylings from which the coded data were initially
factored.
There are a number of distinctive patterns in the results:
(i) Commitment levels do not seem to vary notably with other
variables with the exception of the clustering of casual
intentions with 'looks' and age in female factor 2 and long term
intentions with children in male factor 2.
(ii) For those of both genders, declaring children, there does
not seem to be any distinctive stipulation of partner, or own,
attributes made with the exception of the somewhat trivial joint
loading with divorce in female factor 3.
(iii) On the general subject of looks; males offer own wealth
and looks in exchange whilst females offering looks do not appear
to typically describe distinctive patterns for their potential
partners. Females offering looks show a coupling with casual
intentions whilst males do not. In female factor 7, the demand
for male looks does not couple with any other attributes although
this may just reflect the low incidence of female demands for
looks per se although it must be borne in mind however that we
have used a publication with a very socially conservative
readership to construct the data. This was further investigated
with a simple Chi-squared test for association between PHYSOU
recoded as a binary variable (=1 for some desire for physical
assets) and FINSOU. The value for this was 4.435 which is
significant at the 0.035 level indicating some 'buying beauty'
behaviour as traditionally found for males. Some additional
exploration with logit models to predict the recoded PHYSOU
variable also generated significant results (around the 6% level
on a one-tailed test) for FINOFF when a range of other variables
were included. There is no reciprocal offer of a pure male
physical attractiveness (i.e. youth and beauty offered in
exchange for female resources) archetype .
(iv) The first factor for both genders, and many of the others,
is indicative of similarity, and consumption orientation, which
contradicts the trade specialization metaphor put forward in the
analysis of relationships (essentially marriage ) put forward by
economists following Becker (1973,1974).
V.Discussion
Evolutionary psychological theories of partner preferences
suggest that women seek resourceful mates whilst men seek
attractiveness. This has been supported in studies of personal
advertisements which have mainly used U.S. data. Our data are
from an English national newspaper. The simple univariate
descriptive analysis, as in the literature, confirms the
importance of these factors. However, the factor analytic
treatment does suggest some broader relationship dimensions and
also hints at different weights given to the traditional
male/female exchange components than might be imagined.
The factor analytic treatment shows distinct differences
between the male and female advertisements as we would expect
according to the idea of sexually dimorphic strategies
(Thiessen,D.,Young,R.K. & Burroughs,R.,1993). The contribution
of buying beauty in the male analysis is weak compared to the
corresponding offer in the female analysis in that the factors
are fourth and second contributing 13.2 and 8.3 % respectively.
Turning to the family oriented patterning we may discern
some indication of strategic behaviour. It can readily be
inferred from the small percentage of children declared, and is
well known anecdotally, that many individuals do not declare
their children until contact is made with the respondent. This
may be a characteristic of the type of publications analyzed in
the literature as we have recently inspected local 'freesheet'
newspapers, in the UK, and found a very high incidence of child
declaration by women. Comparing factor 2, in the male analysis,
with factor 3 in the female analysis both show family orientation
but the male majors on long term commitment as opposed to divorce
declaration. This might suggest that females feel constricted
from expecting long term commitment, from men, when they
explicitly reveal that they are divorced with children whilst men
do not.
Whilst the results of this paper are tentative they are
nonetheless suggestive. It is somewhat surprising that previous
workers, in this field, have not deployed the techniques used
here to examine differences in strategy profiling amongst users
of personal advertisements. The most striking feature is the
difference in strategies by gender. Some of these conform to the
expectations of evolutionary psychology whilst others are
indicative of some notable break from the genetic leash.
There are obvious limitations to this kind of work in terms
of the representativeness of the sample and the meaningfulness
of the coding categories. There are some additional problems.
Technology is having a major impact on the strategies of those
who use formal methods of searching for a mate. In recent years,
the lengthy paid advertisement, as analyzed here, has declined in
favour of the short 'free' placement backed up by a premium rate
telephone line. It is obvious that future work on mate selection
needs to take account of telephonic strategy, in information
revelation, consequent to old style textual advertisement. There
is also an increasing emphasis on photographs, notably through
faxing, which should alter text structuring strategy.
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TABLE 1 Variable means by gender for advertisements
MALES FEMALES
sample size 140 119
MEANS
estimated own age in years (AGE) 42.8 41.5
description of own physical attributes(PHYOWN) 1.39 1.43
description of physical attributes sought(PHYSOU) 1.14 0.43
amount spent on the advert in pounds sterling (PRICE) 106.9 96.86
seeks ambiguous relationship(AMBIGUOU) 0.271 0.223
seeks casual relationship (CASUAL) 0.414 0.277
seeks longterm relationship (LONGTERM) 0.279 0.328
seeks platonic relationship (PLATONIC) 0.043 0.168
stipulates expensive leisure interests(EXPOWN) 0.221 0.219
seeks partner with expensive leisure interests(EXPSOU) 0.086 0.101
offers finance (FINOFF) 0.8 0.454
seeks finance from partner (FINSOU) 0.143 0.538
stipulates 'sophisticated' leisure interests (SOPHOWN) 0.24 0.168
seeks partner with 'sophisticated' leisure interests 0.07 0.05(SOPHSOU)
stipulates sporting interests (SPOROWN) 0.17 0.16
seeks partner with sporting interests(SPORSOU) 0.036 0.042
seeks partner with similar interests(TRAITS)
declares having children (CHILDREN) 0.0286 0.167
declares having divorced (DIVORCED) 0.0643 0.246
declares being single(SINGLE) 0.107 0.31
Table 2 Quartimax rotation for female advertisers
Factor 1 Factor 2 Factor 3 Factor 4 Factor 5
AMBIGUOU -.00133 -.04943 -.05869 .20141 .89595
AGE .01383 -.74074 -.06724 .02206 -.01465
CASUAL .02474 .54245 -.26173 .49040 -.44147
CHILDREN -.10933 .29133 .66196 -.18090 -.01249
DIVORCED -.08287 -.07516 .73404 -.05165 -.05792
EXPOWN .65372 -.19565 .11115 .11510 .01388
EXPSOU .81991 -.01419 .16556 .23271 -.03678
FINOFF .11863 -.13091 .10953 .11155 .24472
FINSOU -.10791 .13707 .09257 -.00881 -.14007
LONGTERM -.08121 .02038 .18773 -.91431 -.22254
PHYOWN .03171 .66584 .32909 .21027 -.16029
PHYSOU .06743 .22513 -.01978 -.02080 -.05428
PLATONIC .05730 -.65418 .14531 .35770 -.18250
PRICE .26306 .18315 .43754 -.03621 .12435
SINGLE -.09310 -.00922 -.15764 .00632 -.10795
SOPHOWN .58519 -.20529 -.14379 -.09465 -.09909
SOPHSOU .85203 -.01450 -.02772 -.00648 -.02743
SPOROWN .39232 .27927 -.10179 -.31675 .42335
SPORSOU .70054 .19299 -.15278 -.12971 .18951
TRAITS .64309 .11992 -.08451 .03099 -.03711
Factor 6 Factor 7AMBIGUOU .04000 .01479
AGE .07279 -.06909CASUAL .17347 .16010
CHILDREN -.01971 -.24920DIVORCED .15005 .12687
EXPOWN -.24453 .22515EXPSOU -.02611 .18838
FINOFF .67157 .29218FINSOU .82634 -.06507
LONGTERM -.04946 .04683PHYOWN .08824 .00271
PHYSOU .07685 .82805PLATONIC -.13215 -.27529
PRICE .10027 .40985SINGLE .11715 -.04229
SOPHOWN -.21403 .00229SOPHSOU .07528 .04283
SPOROWN -.08637 -.11674SPORSOU .06125 -.07998
TRAITS .25434 -.26900
TABLE 3
Communalities and factor orderings for females
Variable Communality Factor Pct of Var Cum Pct
AGE .57652 1 18.2 18.2
AMBIGUOU .89620 2 13.2 31.4
CASUAL .86184 3 9.2 40.6
CHILDREN .65352 4 8.0 48.5
DIVORCED .57878 5 7.5 56.0
EXPOWN .62797 6 5.9 61.9
EXPSOU .77408 7 5.4 67.3
FINOFF .66181
FINSOU .73168
LONGTERM .93423
PHYOWN .61493
PHYSOU .69067
PLATONIC .71745
PRICE .54906
TRAITS .59141
SOPHOWN .48251
SOPHSOU .72022
SPOROWN .51014
SPORSOU .61823
TABLE 4 Quartimax factor rotation for male advertisers
Factor 1 Factor 2 Factor 3 Factor 4 Factor 5
AMBIGUOU .07524 -.30832 -.03272 .02937 .03518
AGE .01420 -.02536 .06483 -.05559 .05292
CASUAL -.00633 -.42837 .02569 .14963 -.13250
CHILDREN .03179 .66527 .15641 .15418 .09728
DIVORCED -.04368 .41560 -.13315 .10393 -.11576
EXPOWN .44617 .05031 .73952 .10201 -.12447
EXPSOU -.02216 -.00408 .87187 -.08001 .16733
FINOFF -.10876 .09152 .31902 .64480 -.01675
FINSOU -.05154 .05075 -.06489 .12415 .76652
LONGTERM -.03943 .82513 -.06469 -.20924 .08630
PHYOWN -.00317 -.24851 -.30865 .62160 .23235
PHYSOU .18584 -.00225 -.12207 .54214 -.28908
PLATONIC -.09123 -.08397 .15447 -.00170 .03291
PRICE .51001 .36655 .07849 .45167 .07600
SINGLE -.01439 .02765 -.11597 .06102 .10456
SOPHOWN .82128 -.06750 .20053 -.06196 -.01578
SOPHSOU .42777 -.20937 .32859 -.35646 .29463
SPOROWN .78655 .00738 -.05331 .03482 -.04547
SPORSOU .36367 -.03480 .00608 -.34328 .24938
TRAITS .05163 .07897 .12322 -.10609 .83422
Factor 6 Factor 7 Factor 8
AMBIGUOU -.87490 -.13880 -.20072
AGE -.03188 -.00815 -.03559
CASUAL .80958 -.18806 -.09232
CHILDREN .01928 -.06151 -.22285
DIVORCED -.03774 -.02898 -.35134
EXPOWN -.04405 .05070 -.00685
EXPSOU .09589 .13099 -.11325
FINOFF -.10368 .00879 .16502
FINSOU -.09805 .07881 .12705
LONGTERM .01506 -.05064 .26133
PHYOWN .06609 -.03020 -.10391
PHYSOU .23212 -.18802 -.15009
PLATONIC -.05426 .86205 .09795
PRICE .04931 -.06949 .20121
SINGLE .07808 .01233 .84215
SOPHOWN -.08702 -.23388 .13405
SOPHSOU -.13382 -.26506 -.11851
SPOROWN .02207 .33111 -.17520
SPORSOU .10904 .59574 -.22175
TRAITS .00063 .02369 .00662
Table 5
Communalities and factor orderings for Males
Variable Communality Factor Pct of Var Cum Pct
AGE .81169 1 14.2 14.2
AMBIGUOU .93074 2 11.3 25.5
CASUAL .91407 3 10.2 35.8
CHILDREN .46201 4 8.3 44.1
DIVORCED .36456 5 7.5 51.6
EXPOWN .76801 6 6.8 58.4
EXPSOU .81901 7 6.3 64.7
FINOFF .59741 8 5.7 70.4
FINSOU .67296
LONGTERM .81099
PHYOWN .60804
PHYSOU .58643
PLATONIC .76365
PRICE .65759
TRAITS .70576
SOPHOWN .76732
SOPHSOU .64168
SPOROWN .77291
SPORSOU .72122
TABLE 6 Labels of Rotated Factors by Gender
Male Female
1 Sophisticated, sporty High quality
individual similar consumption oriented
2 Long term and kids young, free and beautiful
3 High quality,similar Divorced with children
consumption oriented
4 Money and shared good looks not long term term
5 wealthy similar woman wanted ambiguous
6 casual relationship wealth seeking wealth
7 platonic relationship handsome man wanted
sought with sporty woman
8 single