Testing Ageing Theory among Later
Middle-aged and Older Users Using Social
Media
Mao Mao
Michal Kosinski
University of Cambridge
Stanford University
Abstract
United Kingdom
United States
[email protected]
[email protected]
David Stillwell
David Good
University of Cambridge
University of Cambridge
United Kingdom
United Kingdom
[email protected]
Research has typically examined the link of activity
patterns and affect among late middle-aged and older
people, in the context of continuity and activity theory.
The aim of this present research was to test continuity
and activity theory among younger employed age (2554), and late middle-age and older age (over 55years
of age) in the online context. We used a sample of
11837 Facebook users to investigate their Facebook
activities. Our results provided evidence for continuity
and activity theory of ageing among Facebook users.
[email protected]
Author Keywords
Age differences; social network; older adults; social
media.
ACM Classification Keywords
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CSCW '17 Companion, February 25 - March 01, 2017, Portland, OR, USA
ACM 978-1-4503-4688-7/17/02.
http://dx.doi.org/10.1145/3022198.3026352
H.5.m. Information interfaces and presentation (e.g.,
HCI): Miscellaneous.
Introduction
It is well established that voluntary activity patterns in
retirement (late middle-aged and older age) is closely
related to affect [6,7]. In the field of gerontology and
retirement, this trend is rooted in activity or continuity
theories. Past research has identified various
Activity Theory
Activity theory was a
homeostatic or equilibrium
model, which suggested that
successful ageing might be
interpreted as continued
adherence to the activities
and attitudes of middle age
to maintain a positive selfconcept.
Continuity Theory
Continuity theory holds that,
by making adaptive
strategies coping with normal
ageing, middle-age and older
people tend to preserve and
maintain both internal and
external continuity structures
to stay coherent to their past
experience from both self and
the social world.
dimensions and types of activity that predict
psychological benefits using self-report scales. Given
that the number of older people going online is
constantly increasing [2], it becomes increasingly
important to explore the link between online activities
and affect in older age. However, little evidence from
social media was present.
Generally speaking, engaging in physical and social
activity improves psychological wellbeing in older age
[4]. The explanation of continuity and activity theory is
rooted in the link between activity engagement and
affect within a particular age range. There is a plethora
of studies on the relationship between age and
emotion, which agreed on the fact that older individuals
are happier than young people. Negative emotion is
negatively associated with age, while the findings on
positive emotion are mixed [3]. In order to take one
step further, exploring activities in relation to affective
outcomes lead researchers to explain the age
differences across age.
According to prior research on decreased activities in
retirement, we propose hypothesis1: The number of
different activities performed and intentions to continue
will decrease. In accordance with activity theory,
engaging in voluntary activities should generate
affective responses [6]. Drawn on continuity theory,
individuals have “preferred levels of voluntary activity”,
and such levels are expected to be stable at earlier
stage of retirement, thus hypothesis 2 predicts that
frequency of activity will be stable across age.
This paper thus aims to explore the link between online
activity and affect, and the age differences and
similarities of this link among Facebook users. We test
the age-related aspect of Continuity and Activity theory
by looking at the relationship between age, activity
parameters, and affect.
Method
This study used data obtained from the myPersonality
application (http://mypersonality.org) on Facebook.
MyPersonality provided users various psychometrics
tests and feedback on their scores. Upon the first use of
the application, participants agree on a consent for the
anonymous use of their test scores and Facebook
profiles. In this study, we collected data from a sample
of 11837 Facebook users. The average age was 32.0,
and the proportion of late mid-aged and older
population (age above 45) was 6%. Participants’ selfreported gender (57.3 % female). In order to perform
comparisons across different age groups within the
positive skewed sample, we used a subset sample
containing 200 younger adults (age 25-55) and 190
mid-aged and older (age above 55) adults.
The data on users’ posts on Facebook was processed
with the Linguistic Inquiry and Word Count (LIWC)
software. The LIWC software counts words with 64
psychologically meaningful categories measuring
functional word use, emotional, cognitive components.
For a detailed description of the LIWC categories, see
the LIWC documentation [5].
We performed multivariate regression on LIWC
categories and age, adjusting for gender. Since we are
performing correlational analysis across many variables
at once, we treat coefficients significant if they are less
than a two-sided 𝑝 of 0.001. We test the Activity theory
assumption that multiple activity measures influence
positive and negative affect by matching psychological
measures from users’ status updates and activities on
Facebook.
Activity Measures in
this study
Positive/Negative Affect.
We used a language-based
measure to describe positive
and negative affect. We
adopted two LIWC categories:
positive emotion and negative
emotion. For instance, words
such as “love”, “nice”,
“sweet” are categorized as
positive emotion, and words
such as “hurt”, “ugly”,
“nasty” are categorized as
negative emotion.
Facebook activities. The
measurement of users’
activities on Facebook
(number of Likes, Status
posted, Events, Groups,
Photo Tags, and Diads) were
used to measure daily
activities.
Frequency of activities.
The standardized relative
frequency of leisure (e.g.,
“cook”, “chat”, “movie”) in
the LIWC database was used
to measure the frequency of
leisure activities.
Results
We plotted several LIWC categories relevant to activity
variables. We found in Figure 1 that the use of future
tense and positive emotion increased with age,
however, the occurrence frequency of positive emotion
peaks at around 60 years old, and then slightly
decreases as age increases. On the other hand, the
frequency of negative emotions decreases as age
increases, and the trend tends to be stable after the
age of 50. These findings are in line with prior research
on ageing positivity theory, which presents that older
individuals used a greater number of positive words
and future tense words, whereas younger individuals
used a greater number of negative words compared to
older adults [3]. The frequency of mentioning family
and friends increased with age, whereas the occurrence
frequency of work remains relatively stable after the
age of 35 (Figure 2). This finding is in line with the
study of Kern et al. [3].
Testing ageing theories
We tested whether the differential language analysis
can be used to test Activity Theory and Continuity
Theory. Kruskal-Wallis test comparing the mean scores
for Facebook activities revealed significant change
across time. The number of joined Facebook group,
number of status post, number of diads, and number of
photo tags decreased significantly, 𝜒 2 = 5.54, 𝑝 < 0.05;
; 𝜒 2 = 17.102, 𝑝 < 0.01; 𝜒 2 = 9.64, 𝑝 < 0.01; 𝜒 2 = 53.52, 𝑝 <
0.01 , respectively. However, the number of likes, and
number of events that user participated did not show
significant results between to younger and older group.
The results indicated that online activity using Facebook
decreased significantly with age, which partially support
our first hypothesis that the number of activity
decreased with age as people move from the stage of
employment to a new stage of retirement.
Scores on negative emotion significantly decreased with
age, 𝜒 2 = 24.57, 𝑝 < 0.001, whereas scores on positive
emotion did not change significantly. This is in line with
the study of Pushkar et al. [6]. We found no significant
results in the frequency of mentioning leisure-related
words across age, which indicated that in our case the
frequency of activity remained stable across age. Based
on continuity theory, which hypothesizes that people
tend to perform activities at an expected level.
Therefore, our results provide some support on
continuity theory in terms of online activity and
language extracted from social network sites.
Discussion and Conclusions
In line with prior findings on decreased activities in
older age, we found the same trend in online activities
among older Facebook users. In support of continuity
theory, our results are consistent with previous findings
relating decreased activity measures across age and
unchanged frequency of activity across age [6]. Both
demographic variables and activity measures account
for the changes in affect.
Our findings highlighted the feasibility and advantages
of social media data in studying ageing. As one step
further after the adoption of new Information and
Communication Technologies, online activities and selfdescriptive texts on social network sites provide a
valuable source in understanding ageing and testing
ageing theories.
Figure 1: Occurrence frequency of LIWC categories across age
(emotion, future tense).
Figure 2 Occurrence Frequency of LIWC categories (family,
friends and work)
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