1. Kwabena Frimpong Supervisors: Dr. Barbara Czarnecka Dr. Giuseppe Adamo
Full Title: That’s my opinion: younger consumers’ perception of older models in newspaper adverts.
Kwabena Frimpong
Supervisors:
Dr. Barbara Czarnecka
Dr. Giuseppe Adamo

2. Rational for Paper
The topic of how the advertising community engages the older consumer group is gaining scholarly attention.
Existing knowledge on how this consumer group is portrayed in ads have largely emanated from opinion of older people themselves ( either as coders or survey participants)
Thus, there is a paucity of knowledge on how the future generation (younger people) perceive the older generation in newspaper adverts.

3. Research Method used
Content analysis of newspaper advert was employed in the study.
The method is largely considered as the most preferred method for studying media content (Krippendorf,2013)
UK newspaper are categorised into 3 – higher quality, mid – quality and the populars (Cridland, 2009)
Using data for NRS( 2010) and Mori Data (2010), a years’ edition of adverts from one higher quality (Telegraph) and two mid- quality (Daily Mirror & Daily Express) newspapers

4. Research Method used
A total of 950 editions of the three newspapers were scanned for a minimum of ¼ page adverts featuring models of all ages
Duplicates from the same publication was omitted.
Finally, 700 adverts were extracted and coded by two young ( 26 & 28 years) coders.

5. Table 1: Breakdown of newspapers / adverts in the study.

6. Table2 – General overview of results
Number of ads. coded
Number of people in ads.
Number of 50’s
In ads.
(Kappa=0.85)
Gender
(Kappa = 0.92)
Count of
% of total
Male
Female
Coder 1
700
2456
346
14%
191
(55%)
155
(45%)
Coder 2
355
186
(52%)
169
(48%)
Mean
350
(53%)
162
(47%)

7. Table3 – Traits in datasets
 Total traits
Positive Traits
(Kappa = .81)
Negative traits.
(Kappa = .92)
Count %
of total
Coder 1
633
592
94% 41 6%
Coder 2
482
92% 24 8%
Mean
537
93% 32 7%

8. Chart 1 – traits in datasets

9. Chart 2 - key positive traits
Figure 1: Trait description uncovered in dataset

10. Chart 3 – key negative traits

11. Table 4 – roles played Roles (Total) Major Minor Background Kappa Mean
Roles
(Total)
Major
Minor
Background
Kappa
Count %
of total
0.89
Coder 1
346
318
92% 18 5% 10 3%
Coder 2
355
319
90% 31 9% 5 1%
Mean
350
91% 24 7% 8 2%

12. Summary – Traits
Older models are positively than negatively portrayed (93% vs. 7%) according to the study
Younger people may perceive older in adverts as representing a “well – informed” demographic group.
This contradicts most of the extent studies (e.g. William et al. 2010;) which have reported the “Healthy”, “ Active” and “ Affluent” traits as typifying the older consumer cohort

13. Summary – Numeric representation
Over 50’s in UK constituted about 36% of the 2014 UK population (ONS, 2014)
a representation of 14% of older models in the study can thus, be considered as an under-representation
There were more males than females ( 53% vs. 47)

14. Summary - Roles played
Both coders were consistent on the fact that older people played major roles more than the other roles.
The significant results as far as ‘role’ is concerned is that both coders found older females (56%) playing more major roles than males (44%) which was a departure from the existing knowledge.

15. Key research questions
What are the traits younger consumer’s perceive older people to be associated with in UK newspaper adverts?
Do younger consumer's think older people are adequately represented in ads?
What are the roles older people mostly play when they feature in advert?

16. Contribution of the paper
Older people could help authenticate a brands’ credibility / quality when used as models.

17. Conceptual Framework Environmental stimuli created by
Advertising community
Image portrayed by older models
Roles older people play (major, minor, background)
The numeric representation of older models in ads.
Results of consumption of media images
misrepresentation of younger people’s world view of old age
Society likely to respond to inappropriate portrayal with some punitive reactions such as product boycott
Media as a mirror to consumers
Ad. audience
Younger consumers
Older consumers
Theoretical model: author's creation based on cultivation theory (Gebner, 1960) and the ethnolinguistic vitality theory (Giles et al. 1977)

18. Appendix - adverts