The influence of social media on people’s life

Understanding the influence of
social media on people’s life
satisfaction through two
competing explanatory
mechanisms
Liuhan Zhan, Yongqiang Sun and Nan Wang
Wuhan University, Wuhan, China, and
Xi Zhang
Tianjin University, Tianjin, China
Abstract
Purpose – The purpose of this paper is to explore how social media usage affects people’s life
satisfaction through two competing explanatory mechanisms.
Design/methodology/approach – An online survey was conducted to collect data. And the partial
least squares method was used to examine the relationships among the usage of social media, social
benefit, social overload and life satisfaction.
Findings – The results indicate that usage of social media can make people achieve social benefit, thus
leading to enhanced life satisfaction. Unexpectedly, though usage of social media can bring the
negative consequences (e.g. social overload), social overload cannot predict a decreased life satisfaction.
Originality/value – Concentrating on the outcomes of social aspects by using social media, this study
proposes the double-sided role of social media instead of single effect.
Keywords Survey, User behaviour, Social media, Life satisfaction, Social benefit, Social overload
Paper type Research paper
1. Introduction
With the development of Web 2.0 technology, social media has permeated almost every
aspect of people’s lives. Especially in recent years, due to its own advantages, social
media has been experiencing a rapid rise. Social media is becoming an essential part of
people’s daily life and a prevailing tool of developing and maintaining relationships
(Elphinston and Noller, 2011). On the one hand, social media breaks the constraint of
space and time, allowing individuals interact anywhere and anytime. Convenient and
diverse forms of communication make people’s social life more colorful, providing users
various choices for connecting and getting familiar with friends, even strangers. On the
other hand, there are more individuals becoming dependent on social media, which may
induce numerous beneficial and detrimental outcomes of people’s physical and
psychological life (Porter et al., 2012).
Most people are constantly pursuing high life quality, seeking an enhanced wellbeing. Life satisfaction is a cognitive and judgmental progress, which reflects a
subjective and global evaluation of a person’s quality of life (Diener et al., 1985). The
Aslib Journal of Information
Management
Vol. 68 No. 3, 2016
pp. 347-361
© Emerald Group Publishing Limited
2050-3806
DOI 10.1108/AJIM-12-2015-0195
Received 8 December 2015
Revised 29 February 2016
Accepted 14 March 2016
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/2050-3806.htm
The work described in this paper was supported by the grants from the National Natural Science
Foundation of China (Project No. 71201118, 71201155, 71571133) and the Fundamental Research
Funds for the Central Universities (Project No. 410500133).
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social media
presence of social media has deeply changed people’s life style, thus may change their
attitude and judgment about life. Extant literatures have examined the effects of social
media on people’s life satisfaction, but the results are still ambiguous (Ang et al., 2015;
Best et al., 2014; Kalpidou et al., 2011). Some scholars contended that using social media
could enhance people’s life satisfaction (Liu and Yu, 2013; Nabi et al., 2013), while some
studies proposed negative relationship between using social media and life satisfaction
(Brooks, 2015; Chou and Edge, 2012). To interpret the inconsistent findings, we
postulate that the underlying effect mechanism may be double-sided, while what the
previous studies considered is partial. Therefore, in this study we will put forward a
more comprehensive set of hypotheses to address the research gap.
Compared with other media, social interaction is a principal component of social
media (Wang et al., 2012). Social needs are recognized as the dominant driving forces
for individuals to use social media (Wang et al., 2012). The usage of social media for
social purpose is more pertinent to individuals’ well-being than other purposes
(e.g. information and entertainment) (Huang, 2010; Wang et al., 2014). Therefore, the
primary concern of this study is about the outcomes of social aspects by using social
media. The present study focusses on two opposite outcomes of social media usage,
i.e., social benefit and social overload specifically.
This study makes several theoretical contributions. Focussing on the social effects
of social media, this study provides a new angle for scholars to better understand the
relationship between social media and life satisfaction. Moreover, it proposes the
double-sided role of social media instead of a single effect, which presents a more
synthetic account of social media usage and life satisfaction.
The rest of the paper is structured as follows. First, we review prior related studies
and then present the theoretical foundation for this study, explaining the perspective of
social benefit and social overload. Then we put forward the research model and develop
the hypotheses. Next, we describe the research methodology and the analysis of the
results. Finally, we discuss the results and give implications for theory and practice.
2. Theoretical background
2.1 Related studies
Research on subjective well-being has achieved prolonged and in-depth studies in
psychology and philosophy, while the exploration of life satisfaction has begun to
attracted scholars’ attention only in recent years (Lim and Putnam, 2010). With the
penetration of social media, it has been a heated discussion about how social media
influences people’s lives.
Extensive studies have examined the effects of social media on well-being, but the
results were still mixed (Best et al., 2014; Chan, 2014). Some studies proposed that using
social media can positively impact individuals’ life satisfaction (Ang et al., 2015; Nabi
et al., 2013; Valenzuela et al., 2009); but others found harmful effects of social media
(Brooks, 2015; Chen and Lee, 2013; Chou and Edge, 2012) (see Table I). The
controversial effects of social media may be due to the different influencing
mechanisms. Everything has two sides, and so has social media. Social media can
enhance people’s life satisfaction through the benefits of increased social capital,
perceived social support or increased self-esteem, etc. (Best et al., 2014), while its
detrimental effects may be depression, social anxiety, jealousy, etc. (Best et al., 2014).
Several mainstream opinions have expounded the positive influences of using social
media. Social support is one of the most common outcomes of social media, which is
thought to be a predictive factor of well-being (Kim and Lee, 2011; Liu and Yu, 2013;
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Nabi et al., 2013; Oh et al., 2014; Sarriera et al., 2012). The usage of social media can help
facilitate interpersonal relationships (Liu and Yu, 2013) and increase supportive
interaction (Oh et al., 2014), thus enhancing users’ perceived social support. On the one
hand, social support can reduce individuals’ perceived stress (Nabi et al., 2013) and
Literature Context
Independent
variables
Dependent
variables
Interaction
effects Theory
Positive effect
Ang et al.
(2015)
Computermediated
communication
Attitude toward
online
relationship
formation (ATO)
Internet habit
strength (IHS)
Online
communication
(OC)
Online selfdisclosure (OSD)
Psychological
need satisfaction
in online
friendships (PNS)
Life satisfaction
(LS)
ATO → PNS
IHS → PNS
OC → PNS
OSD → PNS
PNS → LS
Uses and
gratifications
Self-determination
Nabi et al.
(2013)
Online social
networks
Number of
Facebook
friends (NFF)
Perceived social
support (PSS)
Perceived stress
(PS)
Physical illness
(PI)
Psychological
well-being (PWB)
NFF → PSS
PSS → PS
PS → PI
PS → PWB
Cognitivephenomenological
theory of stress
Valenzuela
et al. (2009)
Social
network
sites
Intensity of
Facebook use
(IFU)
Intensity of
Facebook
groups use
(IFGU)
Life satisfaction
(LS)
Social trust (ST)
Civic
participation (CP)
Political
participation (PP)
IFU → LS
IFU → ST
IFU → CP
IFGU → CP
IFU → PP
IFGU → PP
Social capital
theory
Negative effect
(Brooks,
2015)
Classroom task
environment
Social media
usage (SMU)
Attentional
control (AC)
Multitasking
computer self
efficacy (MCSE)
Task
performance (TP)
Technostress
Happiness
SMU → TP
SMU × AC → TP
SMU × MCSE → TP
SMU → technostress
Technostress → happiness
SMU → happiness
Distractionconflict theory
Chen and
Lee (2013)
Social
networking
sites
The frequency
of Facebook
interaction (FFI)
Communication
overload (CO)
Self-esteem
Psychological
distress (PD)
FFI → PD
FFI → CO
CO → PD
FFI → self-esteem
Self-esteem → PD
na
Chou and
Edge (2012)
Facebook More involved
with using
Facebook (IUF)
Including more
strangers on
Facebook (ISF)
Others have a
better life (OBL)
Others are
happier (OH)
Life is fair (LF)
IUF → OBL
IUF → OH
IUF → LF
ISF → OBL
ISF → OH
ISF → LF
na
Table I.
Related studies on
social media and life
satisfaction
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social media
induce positive affect (Oh et al., 2014), leading to an enhanced life satisfaction. On the
other hand, online social support can reinforce individuals’ offline social support, both
of which can positively influence the perception of well-being (Liu and Yu, 2013).
Besides, owing to the convenience for communication, using social media can promote
social capital (Ellison et al., 2007; Valenzuela et al., 2009), enhance the degree of
perceived connectedness and reduce the degree of perceived social isolation (Ahn and
Shin, 2013), thereby obtaining a high life satisfaction.
However, some researches contended that social media can negatively influence
people’s life satisfaction through some harmful outcomes. Brooks (2015) argued that
using social media can bring technostress and decreased task performance, negatively
related with happiness. Chen and Lee (2013) supposed that interaction on social media
can result in communication overload and decreased self-esteem, then cause
psychological distress. In addition, Chou and Edge (2012) claimed that social media
users are more likely to compare their lives with others, so they are more likely to
perceive a low life satisfaction.
It can be seen that the underlying mechanisms remain ambiguous, hence the
relationship between usage of social media and life satisfaction still deserves research
effort. Focussing on the two contradictory specific outcomes of social media usage, this
study will explore the relationships among usage of social media, social benefit, social
overload and life satisfaction.
2.2 Social benefit
Social activities are a necessary part of people’s everyday life, especially in the internet
environment. Social needs are the basic needs of human beings, and people are inclined
to meet their needs and improve their satisfaction (Steverink and Lindenberg, 2006).
In other words, people anticipate that they can acquire benefits from social activities.
Kuo and Feng (2013) contended that social benefit stems from developing and
maintaining relationships with others such as friendship, intimacy and social support.
That is to say, the benefits can be obtained from close relationships as well as from
newly developed ones. When people gain social benefits, they have better
communication and interaction with other people, and get a broader interpersonal
network, and also perceive social support from others (Kuo and Feng, 2013). Moreover,
social benefit can enhance individuals’ sense of belonging (Kuo and Feng, 2013) and
motivate their intentions to participate (Dholakia et al., 2004). Viewing social benefit as
a positive consequence of social media usage, this study will examine whether social
benefit can have effects on people’s life satisfaction.
2.3 Social overload
Social media have enriched people’s ways of communication and interaction, making it
simple and convenient to develop and maintain relationships. However, as an
individual’s social networks broadens, it increases the probability that the social media
user will receive more social requests, which may lead to the emergence of social
overload (Maier et al., 2014). According to Maier et al. (2012, 2014), social overload
describes the situation when social media users face too many others’ social demands
and feel that they provide too much social support.
Social overload is the negative product of using social media. As social media can
facilitate easy interactions, asking for social support does not need much cost.
Consequently, it increases individuals’ disclosure of their lives online (Maier et al., 2014).
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Under this circumstance, out of the responsibility for friends, other users have to deal
with these substantial social requests to maintain relationships (Maier et al., 2012). Too
much intrusion of social requests into individuals’ lives would interrupt their routines
(LaRose et al., 2014), which can induce detrimental psychological and behavioral
consequences (Maier et al., 2014). Social overload might draw individuals into the
situation of emotional exhaustion (Maier et al., 2012, 2014), resulting in users’ social media
fatigue (Bright et al., 2015) and increased intention of discontinuous usage (Maier et al.,
2012, 2014). What’s worse, the status of social overload is recognized as the source of
increased pressure and more frequent health problems, which can produce negative
affect (LaRose et al., 2014). It can be seen that social overload may influence people’s
normal life, thus this study postulates the influences of social overload on life satisfaction.
3. Hypotheses
Focussing on the outcomes of social aspects, this study proposes a research model to
explore how social media influences individuals’ life satisfaction. The research model is
shown in Figure 1, and more explanations are presented as follows.
3.1 Usage of social media and social benefit
The development of technology, especially the emergence of social media, has
dramatically changed the way people establish relationships (Sarriera et al., 2012).
Social media provide users with an interactive platform, where users can conveniently
participate in a variety of social activities such as text messaging, vision sharing,
content generation and so forth (Porter et al., 2012). Its rich functionalities and
applications make it easy for individuals to actively interact and communicate with
others, deepening the influences on users’ social life.
Ellison et al. (2007) examined the relationships between the usage of Facebook and
the formation and maintenance of social capital, validating that Facebook usage can
not only help develop bridging social capital, but also can strengthen bonding and
maintaining social capital. In other words, usage of social media can contribute to
maintain the existing relationships with relatives and friends, meanwhile can broaden
people’s social networks. Moreover, social media enables users to present themselves in
an online community. Posting comments and clicking the “like” button can be seen as
the concern and support from other online friends. In addition, prior research (Liu and
Yu, 2013; Oh et al., 2014) found that interaction with friends of social media can help
Usage of social
media
Social
benefit
Social
overload
Life
satisfaction
H1 H2
H3 H4
Figure 1.
Research model
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Influence of
social media
users obtain positive affect and simultaneously make them feel more social support.
Therefore, we expect that the usage of social media can bring users more social benefit.
Hence we hypothesize that:
H1. Usage of social media is positively associated with social benefit.
3.2 Social benefit and life satisfaction
Individuals who have higher quality of friendships and extended social group may also
have higher well-being about their lives (Best et al., 2014). The usage of social media can
bring users a closer relationship and a broader social range, thus their affection is to be
fulfilled by the feeling of decreased loneliness and the perception of love, understanding
and acceptance (Steverink and Lindenberg, 2006). Likewise, Ang et al. (2015) examined
the relationships between computer-mediated communication and life satisfaction,
demonstrating that friendships obtained online and online communication will meet
individuals’ psychological needs and positively predict life satisfaction.
In addition, the presence of perceived social support can also be beneficial to
people’s life satisfaction (Nabi et al., 2013; Oh et al., 2014; Sarriera et al., 2012). Sarriera
et al. (2012) argued that perceived social support has a positive association with
adolescents’ personal well-being. Similarly, Oh et al. (2014) validated that perceived
social support is the predictive factor of life satisfaction. Further, Nabi et al. (2013)
claimed that social support can enhance well-being by reducing the feeling of stress.
Therefore, this study assumes that social benefit can bring individuals the feeling of
respect and support, leading to a more positive attitude toward their lives. Hence we
hypothesize that:
H2. Social benefit is positively associated with life satisfaction.
3.3 Usage of social media and social overload
Every coin has two sides. Though social media has brought a lot of convenience to
people, it has also led to quite a few annoyances. As the usage of social media can
facilitate easy information disclosure and social interaction, more individuals tend to
present their living conditions in the online community, which call for other users’
praise or assistance. As thus, users have to confront plenty of others’ social requests
when they log on social media. Out of the responsibility for friends, they may compel
themselves to deal with the massive social requests to amuse or sympathize others (e.g.
click on the like-button, comment on postings) (Maier et al., 2012). Besides, individuals
who have more online friends and use social media more frequently would encounter
and handle more social demands (Maier et al., 2014). When a person gives too much
social support, he or she would feel overburdened or strained, which matches the
description of social overload (Maier et al., 2014).
From the above, the usage of social media may disrupt people’s normal social
life, thus social media seems to be a kind of source of social overload. Hence we
hypothesize that:
H3. Usage of social media is positively associated with social overload.
3.4 Social overload and life satisfaction
When individuals perceive the stress from social activities, they have got into the state
of social overload. It has to take an amount of time and energy to passively maintain
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the mutual relationships with friends (Kim and Lee, 2011), which may trigger negative
emotions and disaffection with the status quo. Besides, social overload can result in
affective fatigue and exhaustion (Maier et al., 2012, 2014, 2015). Scholars (Maier et al.,
2012, 2014, 2015) validated that social overload will be harmful to people’s mental
health, such as emotional exhaustion and decreased satisfaction of their social
activities. Furthermore, individuals will be tired and dissatisfied with their social
condition after experiencing the stress and exhaustion, leading to a series of adverse
effects on living and working (Charoensukmongkol, 2015). Therefore, this study posits
that social overload will reduce people’s life satisfaction. Hence we hypothesize that:
H4. Social overload is negatively associated with life satisfaction.
4. Methodology
4.1 Research setting
To test the research model of this study, an online survey was conducted to collect data.
WeChat users in China were chosen as target population. WeChat is one of the typical
applications of social media. Its basic function is interacting with others. Besides text
messages, users can also send voice messages, videos and pictures to one or more
friends. At the same time, users can make new friends through location-based plug-ins
such as Shake, Look Around and Drift Bottle. In addition, the function of Moments
allows users to share their lives and emotions, which can also help promote interaction
with others. Furthermore, it also provides functions like Public Number and News
Feed, which can basically meet users’ needs for communication and obtain information.
By the first quarter of 2015, over 90 percent of smartphones had installed WeChat
app, and monthly active users had reached 549 million[1]. WeChat has become an
indispensable social tool in people’s daily lives, and using WeChat has become
people’s habits and customs. WeChat has covered a broad range of population in
China and profoundly influenced users’ social life, thus it is suitable to implement
this investigation.
4.2 Measurement
All the measurement items were adapted from extant literatures. To fit the particular
research context, some terms were slightly changed. The items used in this study are
shown in Table AI.
Specifically, the scales for usage of social media were adapted from Ellison et al.
(2007). This instrument includes six reflective items, measuring the extent to which the
users were emotionally related to WeChat and the extent to which WeChat was
integrated into users’ daily life. Social benefit was assessed drawing on the instrument
from Kuo and Feng (2013). This instrument consists of three reflective items, which
reflect the improvement of friendship and intimacy. To assess social overload, we used
the scales adapted from Maier et al. (2015). Six reflective items can reflect users’
negative perception of WeChat usage when they feel that they are giving too much
social support to others. The scales for life satisfaction were adapted from Diener et al.
(1985). This instrument reflects individuals’ global assessment of their quality of life
and it is measured through five reflective items. All items were measured using a
seven-point Likert scale, ranging from “strongly disagree” to “strongly agree.”
To ensure the face validity of the measurement items, four graduate students were
invited to check the initial set of items and give suggestions for revision. As the
respondents were from China, we translated all the items into Chinese. Then the four
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graduate students reviewed and revised the improper expressions to help ensure that
respondents can understand the questionnaire.
4.3 Data collection
The samples were obtained by using the service of an online survey platform, which
was hosted on Wenjuanxing (www.sojump.com). The survey spanned two weeks,
during which a total of 312 WeChat users participated in this investigation. After
deleting the unqualified responses (e.g. multiple responses from the same IP address,
responses missing information and including the same values), 263 valid samples were
retained. Table II shows the demographic information of the respondents. Most
respondents were female (68.44 percent) and aged 18-25 years old (74.14 percent).
In terms of usage experience, most respondents had used WeChat for over 12 months
(82.89 percent). Besides, most respondents had less than 100 WeChat friends
(49.43 percent) followed by respondents with 100-200 WeChat friends (31.94 percent).
5. Data analysis
The partial least squares (PLS) method was chosen to examine the research model.
First, as one of the structural equation modeling technique, PLS can estimate the
parameters for relationships between measures and constructs and the relationships
among constructs at the same time (Hulland, 1999). Second, PLS does not have rigorous
restrictions on variable distributions (Wang et al., 2015). Additionally, it is applicable
for models with small as well as large samples, and formative as well as reflective
constructs (Hair et al., 2011). For all the reasons above, PLS seems suitable in this study.
Thus, SmartPLS was used to conduct data analysis.
5.1 Measurement model
The measurement model is assessed by examining the reliability, convergent validity
and discriminant validity. The criteria of reliability were proposed as composite
reliability (CR) of 0.70 or above and indicator loadings of 0.70 or above (Hair et al., 2011).
As shown in Table III, the CR of each construct ranges from 0.907 to 0.938, all above the
recommended threshold. Besides, from Table IV, we can see that all item loadings are
Variables Category Distribution %
Gender Male 83 31.56
Female 180 68.44
Age Under 18 6 2.28
18~25 195 74.14
26~30 41 15.59
31~40 6 2.28
Above 40 15 5.70
Usage experience Under 3 months 11 4.18
3~6 months 9 3.42
6~12 months 25 9.51
Above 12 months 218 82.89
Number of WeChat friends Under 100 130 49.43
100~200 84 31.94
200~300 34 12.93
Above 300 15 5.70
Table II.
Respondent
demographics
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higher than the threshold of 0.70 except LS5 (0.644). Considering that only one
loading is slightly lower than 0.70, it was still retained for sound theoretical reasons
(Hulland, 1999). Thus we may say that the measurement model satisfies the
requirements of reliability.
Construct Item Mean SD CR AVE
Usage of social media (USM) USM1 5.48 1.427 0.938 0.716
USM2 5.38 1.398
USM3 5.50 1.493
USM4 4.64 1.719
USM5 4.79 1.600
USM6 5.10 1.628
Social benefit (SB) SB1 4.78 1.291 0.911 0.775
SB2 5.08 1.258
SB3 4.48 1.345
Social overload (SO) SO1 3.72 1.400 0.907 0.620
SO2 3.97 1.369
SO3 3.57 1.385
SO4 4.00 1.386
SO5 4.65 1.414
SO6 4.25 1.539
Life satisfaction (LS) LS1 4.63 1.125 0.918 0.694
LS2 4.57 1.133
LS3 4.57 1.196
LS4 4.33 1.282
LS5 3.35 1.608
Notes: SD, standard deviation; CR, composite reliability; AVE, average variance extracted
Table III.
Psychometric
properties
of measures
USM LS SB SO
USM1 0.835 0.250 0.404 0.335
USM2 0.820 0.279 0.449 0.371
USM3 0.893 0.328 0.425 0.388
USM4 0.815 0.201 0.452 0.521
USM5 0.881 0.260 0.520 0.464
USM6 0.830 0.198 0.486 0.419
LS1 0.286 0.831 0.243 0.175
LS2 0.290 0.899 0.301 0.143
LS3 0.293 0.913 0.273 0.117
LS4 0.208 0.851 0.254 0.194
LS5 0.111 0.644 0.146 0.124
SB1 0.490 0.265 0.912 0.544
SB2 0.546 0.309 0.910 0.515
SB3 0.373 0.203 0.816 0.507
SO1 0.361 0.066 0.437 0.800
SO2 0.452 0.159 0.501 0.785
SO3 0.362 0.162 0.441 0.857
SO4 0.336 0.162 0.510 0.800
SO5 0.450 0.128 0.420 0.761
SO6 0.362 0.160 0.474 0.715
Notes: USM, usage of social media; LS, life satisfaction; SB, social benefit; SO, social overload
Table IV.
Loadings and crossloadings of measures
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The convergent validity and discriminant validity were evaluated using
confirmatory factor analysis. For an adequate convergent validity, the average
variance extracted (AVE) should be higher than 0.50 (Hair et al., 2011). As shown in
Table III, all AVE values of each construct are greater than 0.50, indicating a good
convergent validity. The discriminant validity was assessed by examining whether the
square root of AVE for each latent variable is higher than the correlation between the
latent variable and any other latent variable (Fornell and Larcker, 1981). According
to Table V, all square root of AVE values exceed the correlations, demonstrating the
adequacy of discriminant validity. In addition, from the results of Table IV, each item
loading is highly correlated with the intended constructs and greater than all of
its cross-loadings, justifying the good convergent validity and discriminant validity
(Hair et al., 2011).
5.2 Structural model
The PLS results for structural model are shown in Figure 2. As is shown, usage of
social media has a significant positive effect on social benefit ( β ¼ 0.543, po0.01),
supporting H1; social benefit has a significant positive effect on life satisfaction
( β ¼ 0.299, po0.01), supporting H2; usage of social media has a significant positive
effect on social overload ( β ¼ 0.499, po0.01), supporting H3; no significant
relationship exists between social overload and life satisfaction ( β ¼ 0.003, pW0.05),
thus H4 is not supported. Besides, 29.5 percent of the variance in social benefit is
explained by usage of social media; 9.0 percent of the variance in life satisfaction is
Variable USM LS SB SO
USM 0.846
LS 0.296 0.833
SB 0.543 0.300 0.880
SO 0.499 0.179 0.591 0.788
Notes: USM, usage of social media; LS, life satisfaction; SB, social benefit; SO, social overload
Table V.
Correlation matrix
with the square
root of the AVE
in the diagonal
Usage of social
media
Social
benefit
Social
overload
Life
satisfaction
0.543** 0.299**
0.499** 0.003ns
R2
=0.295
R2
=0.249
R2
= 0.090
Notes: *p<0.05; **p<0.01; ns=p>0.05
Figure 2.
Results of the
research model
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explained by social benefit and social overload; and 24.9 percent of the variance in
social overload is explained by usage of social media.
6. Discussion and Implications
6.1 Discussion
This study aims to examine the influence of social media usage on individual’ life
satisfaction. The results reveal some interesting findings.
First, the results show that the usage of social media positively influences social
benefit, indicating that by using social media, users can maintain relationships with
friends. At the same time, they can make new friends and obtain an expanded social
circle. Besides, they can perceive more social support than offline. Second, social benefit
has a positive effect on life satisfaction, suggesting that benefits obtained from social
media can make individuals have a favorable evaluation of their lives. Third, there is a
positive relationship between social media use and social overload. This finding reveals
that people’s social life does not become relaxed through social media. On the contrary,
receiving too many social requests and giving too much social support make individuals
feel stressed. Unexpectedly, social overload does not show a significant influence on life
satisfaction. The results indicate that the pressure from social overload is not enough to
reduce people’s evaluation of their lives. There could be several reasons for the
insignificant influence: some moderators may impact the relationship between social
overload and life satisfaction, for instance personal traits (Hao et al., 2014), self-esteem
(Best et al., 2014) or social skill (Chan, 2014). Besides, as social media has become a part of
daily life, individuals may have been used to the condition of so many social requests.
6.2 Theoretical implications
This study has several implications for research. First, focussing on the outcomes of
social aspects, this study explores how social media influences people’s life satisfaction.
Though studies on the relationships between social media and well-being have
attracted scholars’ attention, prior studies mostly considered the effects such as usage
frequency (Chen and Lee, 2013; Oh et al., 2014), number of friends (Kim and Lee, 2011;
Oh et al., 2014) and personality (Chan, 2014), and so forth. While social need is
necessary, this study contributes a better understanding of outcomes of social media
and tries to clarify the issues related to the mixed findings in extant literatures.
Thus this study provides a new perspective to study the influences of social media on
life satisfaction.
Second, this study takes into account the positive effect as well as negative effect of
social media usage on life satisfaction. It proposes that using social media could bring
people with different feelings of their social life. Serving as a complement of well-being
studies, it attempts to discover multiple influencing mechanisms at the same time
instead of partial explanation. The proposed research model highlights that the
relationship between social media usage and life satisfaction can be either positive or
negative depending on which route is more salient. In our study, although we find both
positive and negative consequences of social media usage, the positive consequences
dominate the overall impact.
6.3 Practical implications
According to the results of this study, usage of social media can positively influence
social benefit, thus leading to an increased life satisfaction. Social networking is
357
Influence of
social media
people’s primary demand, and most people expect to establish comfortable and stable
social relations. With the popularity of the internet and an accelerated life rhythm,
face-to-face communication is unable to meet individual’s social needs. Hence social
media can serve as an appropriate platform for interaction. Users are inclined to choose
the most suitable social media for themselves. As the existence of more alternatives, it
is a challenge for social media providers to keep users. Service providers should
constantly optimize their products to improve the quality of user experience so that
they can retain the existing users and attract new users.
On the other hand, though the negative effect of social media is insignificant, social
overload can produce some adverse outcomes. Maier et al. (2012, 2014) found that
social overload will induce emotional exhaustion and decrease users’ satisfaction of
social media, which can cause users’ discontinuance intention or switch to alternatives.
To prevent users’ discontinuance, service providers should take measures to reduce the
condition of social overload. They can improve the information screening technology,
letting users easily filter the information they do not want to see. In addition, users
should reduce the usage time when they perceive social overload. They can move their
attention to offline activities to relieve the online stress.
6.4 Limitations and future study
In spite of its implications, several limitations should be noticed. First, the
generalizability of the results may be a problem, as only Chinese WeChat users were
involved in the investigation. Future studies should include other types of samples and
different contexts of social media. Second, the measures are self-reported, thus possibly
existing biases may make the results less convincing. Multiple methods should be
utilized in the future studies. Moreover, the lack of correlation between social overload
and life satisfaction is unexpected and limits the significance of this study. In future
studies, the negative effects of social media should be continuously concerned. In other
words, research on social media and life satisfaction still deserve attention.
Well-being and life satisfaction have always been the focus in the field of
psychology and sociology. Social development should not only satisfy individuals’
material necessities, but also enhance their mental satisfaction. As social media has
penetrated into people’s lives, service providers should concern users’ needs and
attempt to create a media that makes people feel real happiness.
Note
1. http://baike.baidu.com/link?url ¼ BvGwpW6I6uVlfYzMt961-z49ava_UPrQA8FedCuGuvF
EEPHiJxKIuPO7_me-VjdLbcRoGAbiccqrZgMuGrk05LdEaqmYXe0uhyNF0V_0eAa
(accessed October 29, 2015).
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360
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Appendix
Corresponding authors
Yongqiang Sun can be contacted at: [email protected]
Nan Wang can be contacted at: [email protected]
Xi Zhang can be contacted at: [email protected]
Variable Item Measurement
Usage of social media (USM)
(Ellison et al., 2007)
USM1 WeChat is part of my everyday activity
USM2 I am proud to tell people I’m on WeChat
USM3 WeChat has become part of my daily routine
USM4 I feel out of touch when I haven’t logged onto WeChat for a
while
USM5 I feel I am part of the WeChat community
USM6 I would be sorry if WeChat shut down
Social benefit (SB) (Kuo and
Feng, 2013)
SB1 I can expand my social network through participation in
WeChat
SB2 The WeChat helps strengthen my connections with other
members
SB3 I can make friends with people sharing common interests with
me in WeChat
Social overload (SO)
(Maier et al., 2015)
SO1 I take too much care of my friends’ well-being on WeChat
SO2 I deal with my friends’ problems too much on WeChat
SO3 My sense of being responsible for how much fun my friends
have on WeChat is too strong
SO4 I am too often caring for my friends on WeChat
SO5 I pay too much attention to posts of my friends on WeChat
SO6 I congratulate WeChat friends as a consequence of the
birthday reminder, although I would not congratulate them in
real life
Life satisfaction (LS)
(Diener et al., 1985)
LS1 In most ways my life is close to my ideal
LS2 The conditions of my life are excellent
LS3 I am satisfied with my life
LS4 So far I have gotten the important things I want in life
LS5 If I could live my life over, I would change almost nothing
Table AI.
Measures of
constructs
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