Being positive and its effect on self-esteem and social needs satisfaction in the presence of social
media feedback
Darrick Chow
Department of Psychology
McGill University, Montreal
August 2014
A thesis submitted to McGill University in partial fulfillment of the requirements of the degree
of Master of Science in Experimental Psychology
© Darrick Chow 2014
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Table of Contents
List of Tables ................................................................................................................................. iv
List of Figures ................................................................................................................................. v
Abstract .......................................................................................................................................... vi
Résumé.......................................................................................................................................... vii
Acknowledgements ........................................................................................................................ ix
Introduction ..................................................................................................................................... 1
Sociometer Theory of Self-Esteem ............................................................................................. 1
Self-Esteem and Online Social Networking ............................................................................... 4
Present Study .................................................................................................................................. 7
Operationalization and Hypotheses ............................................................................................ 7
Method ............................................................................................................................................ 8
Participants .................................................................................................................................. 8
Design ......................................................................................................................................... 8
Materials ..................................................................................................................................... 9
Self-esteem .............................................................................................................................. 9
Daily Measures ....................................................................................................................... 9
Facebook Measures ............................................................................................................... 10
Procedure .................................................................................................................................. 11
Results ........................................................................................................................................... 12
Regression Analyses ................................................................................................................. 12
Multilevel Modeling Analyses .................................................................................................. 17
Discussion ..................................................................................................................................... 20
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Main Findings ........................................................................................................................... 20
Implications............................................................................................................................... 23
Final Remarks ........................................................................................................................... 25
References ..................................................................................................................................... 27
iv
List of Tables
Table 1. Daily Observations As a Function of Facebook Likes and Condition ........................... 33
v
List of Figures
Figure 1. Coder ratings of participants' overall positivity ............................................................ 34
Figure 2. Daily ratings of unpleasant affect ................................................................................. 35
Figure 3. Daily ratings of self-esteem .......................................................................................... 36
Figure 4. Daily ratings of social relatedness ................................................................................ 37
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Abstract
According to Sociometer Theory (Leary, Tambor, Terdal, & Downs, 1995), the
satisfaction of relatedness needs is a critical factor for healthy self-esteem. Online social
networks would seem to provide a convenient platform for people to meet their relatedness
needs, and might offer an opportunity for individuals with low self-esteem to compensate for a
lack of relatedness in their face-to-face interactions. However, previous studies (Forest & Wood,
2012) suggest that people with low self-esteem (LSEs), compared to people with high selfesteem (HSEs), tend to be more negative on online social networks—specifically, Facebook—
which then leads to receiving less positive feedback and others finding them less likable overall.
In the present study, we proposed that LSEs making positive statements on Facebook might
improve their self-esteem but only when receiving positive feedback from others. We recruited
53 participants in a study lasting 2 weeks, where they were asked to either (1) write daily
positive statements on Facebook, where they had the possibility to receive feedback from their
peers, (2) write daily positive statements on a survey, where they would not have the possibility
to receive any feedback, or (3) write daily statements of their choosing (either positive, negative,
or neutral) on Facebook. Our results did not show the predicted improvement in self-esteem after
2 weeks. However, we did find that higher feedback received led to greater feelings of social
relatedness, a vital component to Sociometer Theory. Moreover, using hierarchical linear
modeling analyses, we found that an increase in daily feedback received did lead to an increase
in self-esteem the day after. These findings suggest that online social networks, in this case
Facebook, might be a viable platform for people to meet their relatedness needs, and ultimately
improve their self-esteem.
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Résumé
Selon la théorie sociométrique de l’estime de soi (Sociometer Theory; Leary, Tambor,
Terdal, & Downs, 1995), la satisfaction des besoins d’affiliation contribue de façon significative
à une saine estime de soi. Il est concevable que la plate-forme des réseaux sociaux virtuels
permette aux personnes de satisfaire leurs besoins d’affiliation, en plus d’offrir à celles possédant
une faible estime de soi l’occasion de combler un manque d’affiliation dans leurs interactions
sociales. Toutefois, plusieurs études (Forest & Wood, 2012) suggèrent que les personnes dont
l’estime de soi est faible (FES), relativement aux personnes chez qui elle est haute (HES),
tendent à se montrer plus négatives sur les réseaux sociaux – Facebook, en particulier – ce qui
diminue la quantité de rétroactions positives qu’elles reçoivent et fait en sorte qu’elles sont
moins appréciées par les autres utilisateurs. La présente étude a testé l’hypothèse que les
individus ayant une FES et à qui on a donné l’instruction d’émettre des commentaires positifs sur
Facebook (particulièrement en réaction aux rétroactions positives venant des autres) rapporterait
une amélioration de leur estime de soi. Cinquante-trois (53) participants ont participé à une étude
de 2 semaines, où nous leur avons demandé de se prêter à l’un ou l’autre de ces trois exercices :
(1) écrire quotidiennement des commentaires positifs sur Facebook, où il leur serait possible de
recevoir une rétroaction de leur pairs, (2) écrire quotidiennement des commentaires positifs dans
le cadre d’un sondage, où il leur serait impossible de recevoir une rétroaction, ou (3) écrire
quotidiennement des commentaires de leur choix (positifs, négatifs, ou neutres) sur Facebook.
Les résultats, basés sur deux semaines de collecte de données, n’ont pas mis en évidence
l’amélioration de l’estime de soi que nous prédisions. Toutefois, nous avons observé que le
nombre de rétroactions reçues était positivement corrélé au sentiment d’affiliation sociale, une
composante essentielle de la théorie sociométrique de l’estime de soi. De plus, l’utilisation
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d’analyses de régressions hiérarchiques a révélé que le nombre de commentaires positifs reçus
quotidiennement était positivement corrélé à une amélioration de l’estime de soi le jour suivant.
Ces résultats suggèrent que les réseaux sociaux virtuels (Facebook en l’occurrence), peuvent
servir de plates-formes viables qui permettent aux personnes de satisfaire leurs besoins
d’affiliation sociale, et éventuellement d’améliorer leur estime de soi.
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Acknowledgements
First and foremost I would like to thank my supervisor, Dr. Mark Baldwin, whose
guidance, advice, and encouragement has motivated more than he might realize. I am incredibly
grateful for his patience and understanding, which allowed me to keep pushing through despite
my wavering many times.
Thank you Dr. Hsiu-Ting Yu for your advice and assistance with understanding the
statistical analyses that went into this work. Your explanations were invaluable and saved me
from going down the wrong path a number of times.
I would also like to thank the McGill social psychology faculty and community in general
for their support over the last couple years. All of you have contributed to my sanity at one point
or another. Specifically, I was lucky to have Sébastien Nguyen, Régine Debrosse, and Frank
Kachanoff as colleagues for their support, empathy, and friendship. Thanks for listening to me
when I had something to say.
This project would not have been as efficient or organized without the help of Wayne
Yang, to whom I am very grateful. Thank you to the Facebook transcript coders: Monika
Girnius, Enoch Leung, and Xin Wang.
A special thank you to Nicholas Gardner for providing feedback and advice despite not
really wanting to, but still giving me some of the most useful tips and help.
The love and support from Elizabeth Jin has been the fuel I’ve been running on the last
few months. I would not have finished this without her. As of this writing, she will be starting
her own graduate school journey, so I hope two years from now I will have been as much help
for her as she has been for me. Last but not least, the support of my family has kept me going
when I was feeling the most down. Mom, dad, Darren, and Sandy, thanks for being there.
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Introduction
The effect of others on our individual psyche has long been a topic of interest—
Cooley (1902) and Mead (1934) both hypothesized in the early 20th century that the
individual’s self-concept is shaped by feedback from significant others. With the
exponential growth of the Internet’s user base, feedback from others is increasingly being
received through online social media platforms. This feedback from others may have
implications for individuals’ psychological well-being and satisfaction of psychological
needs. In particular, Sociometer Theory (Leary, Tambor, Terdal, & Downs, 1995)
suggests that self-esteem is derived from feelings of relatedness, acceptance and inclusion
by others (see also Self-Determination Theory, e.g., Moller, Friedman, & Deci, 2006;
Deci & Ryan, 1995, which includes relatedness as a core psychological need). The
current study examined the role of social feedback in the effects of online social media on
relatedness needs satisfaction and self-esteem.
Sociometer Theory of Self-Esteem
Sociometer Theory posits that self-esteem acts as a gauge of an individual’s
relational value—the desirability of the individual to other people (Leary et al., 1995;
Leary & Baumeister, 2000). In other words, Sociometer Theory emphasizes the
satisfaction of relatedness needs. From the sociometer perspective, self-esteem reacts to
social cues that threaten the individual’s acceptance or inclusion in groups or
relationships (Leary, 2005). Thus, individuals with high self-esteem (HSEs) are those
who perceive themselves as desirable, valued, and accepted people, whereas individuals
with low self-esteem (LSEs) are those who perceive themselves as having low eligibility
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for social inclusion (Leary & Baumeister, 2000). Indeed, there is evidence that HSEs tend
to have more satisfying and stable interpersonal relationships than do LSEs (e.g., Leary &
MacDonald, 2003).
According to Sociometer Theory, people are not motivated to maintain their selfesteem per se, but are instead motivated to seek acceptance and to avoid rejection or
exclusion (Leary et al., 1995)—and this can lead to a range of negative outcomes
including chronically low self-esteem. Although there are a number of “conventional”
ways in which LSEs might try to increase their standing in others’ eyes—for example, by
excelling in various domains, being generous, or telling interesting stories—Leary and
his colleagues have noted that LSEs may resort to more destructive behaviours when
their initial efforts to gain acceptance fail (Leary, Schreindorfer, & Haupt, 1995). LSEs,
compared to HSEs, more often display behaviours that present a risk or danger to
themselves, perhaps in an attempt to establish a sense of belongingness—even if it is with
a deviant group (Leary et al., 1995). In some cases, it seems that the desire to avoid
rejection (or to seek acceptance) outweighs the risks involved with certain behaviours.
For example, low self-esteem is associated with substance abuse (Kandel, 1980), unsafe
sex (Holmbeck, Crossman, Wandrei, & Gasiewski, 1994), and eating disorders (Shisslak,
Pazda, & Crago, 1990). LSEs may use drugs or drink alcohol to “look cool” and try to
increase the likelihood of being accepted by others. Indeed, the most prominent
predictors of smoking in adolescence are (a) whether the youth’s peers smoke, and (b) the
desire to be accepted (Botvin et al., 1993). Low self-esteem is also associated with failure
to use contraception during sex (Tashakkori & Thompson, 1992)—a finding that Leary et
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al. (1995) suggest may be due to LSEs’ desires to please their partners. As these studies
suggest, there are real public health risks involved with having low self-esteem.
To further support the Sociometer Theory, Anthony, Wood, and Holmes (2007)
hypothesized that LSEs, but not HSEs, base their social decision-making on acceptance.
Indeed, they found that LSEs were less willing to join a group when faced with a group
that did not guarantee acceptance. Mediation analyses further revealed that anticipated
social outcomes predicted willingness to join a group, but only LSEs’ anticipated
outcomes were significantly affected by acceptance (Anthony et al., 2007).
Perhaps ironically, LSEs’ cautious and self-protective style, characterized by an
unwillingness to accept social risks and a reluctance to draw attention to one’s self
(Baumeister, Tice, & Hutton, 1989), may lead them to shy away from many behaviours
that could improve the closeness of their relationships. For example, LSEs tend to selfdisclose less in-person than do HSEs (Gaucher et al., 2012), which may make it difficult
for them to form strong bonds with others (see Reis & Shaver, 1998).
LSEs are therefore trapped in a cycle whereby the inability to form strong
relationships, sometimes due to their misguided attempts to seek acceptance and/or avoid
rejection, impedes the ability to raise their self-esteem. Perhaps LSEs could adopt a new
approach to their interactions in the context of social media, which might offer a more
controlled and manageable form of communication to allow the individual to find
acceptance. This was a guiding question in the current research.
As a side note, studying social media offers methodological advantages for the
self-esteem researcher. There are common challenges that each of the previous research
findings have faced, particularly with measuring real world behaviour and social
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dynamics. In some of the previous studies, people’s desire to be accepted were observed
through either diary studies, which may have issues with compliance and testing effects
(Iida, Shrout, Laurenceau, & Bolger, 2012), or in-lab studies, which may have issues with
external validity. However, with the emergence of online social media, these challenges
could be eliminated.
Self-Esteem and Online Social Networking
To say Facebook has become ubiquitous around the world would be an
understatement: in June of 2014 alone, Facebook received an average of 829 million
daily active users, with approximately 81.7% of those users being outside of the U.S. and
Canada (Facebook, 2014). The average American mobile device user spends 17% of their
time browsing Facebook—more than any other social networking site (SNS), or any
other single application (Khalaf, 2014).
Facebook not only simplifies communication between large numbers of people,
but it also affords researchers the ability to glean a wealth of information. For example,
we are able to approximate how many people are in an individual’s social network (e.g.,
his or her friends list) or how positively his or her friends see him or her (e.g., the number
of “likes” he or she receives on their postings). Since Facebook is a part of so many
people’s daily routines, researchers have taken notice by investigating the impact that
Facebook has on people’s lives. For example, Gentile, Twenge, Freeman, and Campbell
(2012) investigated the effect of social networking websites on positive self-views—they
found that college students who focused their attention on their Facebook page reported
higher general self-esteem compared to those who interacted with Google Maps. More
recently, Kramer, Guillory, and Hancock (2014) showed that emotional states can be
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transferred to others through Facebook, leading others to experience the same emotions
as others in their network, apparently without their awareness.
As previously noted, LSEs tend to avoid social risks and drawing attention to
themselves, but what about in non-face-to-face situations? Smith and Williams (2004)
found that participants who were ostracized through cell phone text messaging (SMS),
which is similar to online interactions in that it is non-verbal, computer-mediated
communication, reported worse moods and lower state levels of self-esteem.
Interestingly, however, participants who were ostracized also wrote more provocative
messages (e.g., “How come no 1 is messaging me?!!”; Smith & Williams, 2007). The
behaviour exhibited by those that were ostracized supports the notion that targets of
ostracism generally display more courage when the ostracism occurs through a computer
medium, compared to an offline, face-to-face interaction (see Williams et al., 2002),
possibly because they feel that that online communication is safer or risk-free.
Correlational evidence suggests that distressed adolescents may specifically seek
communication with strangers online as a form of counselling, aiming to improve their
mood and sense of belonging (Gould, Munfakh, Lubell, Kleinman, & Parker, 2002).
Indeed, an experiment by Gross (2009) found that, following an induction of social
exclusion, participants showed a greater replenishment of self-esteem and perceived
relational value after online communication with an unfamiliar peer. This finding
provides further evidence as to why an individual may be motivated to seek online
communication.
Smith and Williams (2007), Gould et al. (2002), and Gross (2009) did not
investigate the differences, if any, between HSEs and LSEs with respect to computer-
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mediated interactions. However, Zwyica and Danowski (2008) found that popularity was
valued more by LSEs than by HSEs. In addition, LSEs, compared to HSEs, tend to selfdisclose more about themselves to online friends than they would to offline friends. In
general, LSEs may feel less inhibition online compared to offline and are therefore more
comfortable expressing themselves online rather than offline.
Indeed, Forest and Wood (2012) also found that LSEs consider Facebook a safer
place to express themselves than did HSEs. This finding would indicate that LSEs might
have more success forming relationships through Facebook than they would in-person.
Unfortunately, further investigation shows this to be unlikely (Forest & Wood, 2012).
LSEs, compared to HSEs, tend to share more negativity through Facebook, which made
them be viewed as less likeable by peers. Despite Facebook being a medium in which
LSEs feel safe, then, LSEs still appear unable to benefit therefore continuing the cycle of
lower self-esteem. Forest and Wood (2012) further found that, in contrast with LSEs,
HSEs tended to share more positive things and would receive a greater positive response
from peers (more “likes” and comments).
The research just reviewed leads to the core question of the current study: Can
LSEs satisfy their need for acceptance—and therefore improve their self-esteem—simply
by being more positive on Facebook? Wood, Perunovic, and Lee (2009), in a study of
this type of intervention in the offline world, might suggest that it is not so simple. When
told to repeat positive, self-affirming statements (e.g., “I’m a loveable person”), LSEs,
compared to HSEs, actually experience a worsening in mood and become more selfcritical. Moreover, Josephs, Bosson, and Jacobs (2003) showed that LSEs, compared to
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HSEs, are less likely to accept positive feedback when it was self-generated. However,
LSEs did accept the feedback when it came from a credible, external source.
Present Study
In the research just reviewed it is possible that positive self-statements backfired
for LSEs because LSEs do not see themselves as a “credible source” for affirmative
statements. The statements were made in isolation, without feedback from others (e.g.,
“Yes, you are a loveable person”). Since Sociometer Theory suggests that self-esteem is
linked to one’s perceived relational value, if one perceives one’s value to increase—
through social feedback—the individual should experience an increase in self-esteem.
We suspect that posting more positive things on Facebook may increase LSEs selfesteem but only if they receive feedback from others. In addition, positive self-statements
may have had a detrimental effect in previous research (Wood, Perunovic, & Lee, 2009)
because LSEs were told specifically what to say rather than being allowed to generate
their own self-affirmative statements. Our present study aimed to address these issues by
using the Facebook platform, which allows for the ease of operationalizing positive
feedback from others, as well as allowing people to decide for themselves what positive
things to express.
Operationalization and Hypotheses
Facebook allows its users to share “status updates” as a way of sharing their
thoughts. In offline settings, it can be difficult to operationalize the amount of positive
feedback one receives from one’s peers (e.g., a rejecting smirk versus an accepting
smile). However, positive feedback is easily measured on Facebook, taking the form of
subjective comments written by peers, or the number of “likes” for a given status update.
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A “like” is a concise, one-click method of responding that is available to users as a way
to indicate their liking for various things on Facebook. Therefore, in order to quantify
positive feedback by peers, we can turn to the number of “likes” a status update receives,
and code the comments written by peers for positivity.
In the present study, we predicted that, for those with low self-esteem, increased
positivity on Facebook would increase self-esteem and that the effect would be
moderated by the positive feedback received from peers. Specifically, we predicted that
positivity on Facebook can increase one’s self-esteem only when peers are reaffirming
the positivity. Furthermore, we suspected that people’s self-esteem would be sensitive to
daily fluctuations in feedback received from peers—people’s feeling of self-esteem on a
given day should increase after receiving a lot of positive feedback, but not if receiving
very little or none.
Method
Participants
Participants were 53 students recruited from McGill University who completed
the study in exchange for remuneration. Only participants who indicated in a prescreening questionnaire that they visited and posted on Facebook frequently were eligible
to participate in the study. Ten of the participants discontinued their participation and did
not complete the final questionnaire. A total of 43 participants (30 females, 13 males)
between the ages of mean age = 20.33) were included in the later analyses.
Design
The experiment employed a continuous (self-esteem) × 3 (condition: daily
positive posts with feedback vs. daily positive posts without feedback vs. regular posts
9
with feedback) between-subjects design. Participation in the study took place over a
period of 14 days and participants were asked to complete a daily online questionnaire.
Depending on experimental condition, participants were reminded daily to write a
positive post on their Facebook profile (experimental condition; n = 11), write a positive
post as a response to a survey item outside of Facebook (control condition; n = 16), or
write a regular post of their choosing (i.e., what they might usually post) on their
Facebook profile (base condition; n = 16). The main dependent variables in this study
were: (a) participants’ self-esteem at the end of the study, (b) participants’ daily needs
satisfaction, and (c) participants’ daily affect.
Materials
Self-esteem. At the start of the 2-week study period, participants completed a set
of online questionnaires, including a 10-item measure of self-esteem (Rosenberg, 1965).
Participants indicated the extent to which they agreed with each item (e.g., I take a
positive attitude toward myself,” and “I certainly feel useless at times”) on a 9-point
Likert scale (1 = strongly disagree, 9 = strongly agree).
Daily Measures. For the duration of the 2-week period, participants completed a
set of online measures each night after 6.p.m. Using a 9-point Likert scale (1 = strongly
disagree, 9 = strongly agree), participants were asked to indicate the extent to which they
agreed with the statement “Today I felt…” followed by the items in question. We adapted
items from Sheldon, Elliot, Kim, and Kasser (2001) to measure 6 psychological needs:
1. Autonomy: “that my choices were based on my true interests and values; “that my
choices expressed my ‘true self’”
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2. Competence: “that I was successfully completing difficult tasks and projects”;
“very capable in what I did”
3. Relatedness: “a sense of contact with people who care for me, and whom I care
for”; “close and connected with other people who are important to me”; “a strong
sense of intimacy with the people I spent time with”
4. Self-actualization: “that I was ‘becoming who I really am’”; “a sense of deeper
purpose in life”
5. Security: “glad that I have a comfortable set of routines and habits”; “safe from
threats and uncertainties”
6. Popularity: “that I was a person whose advice others seek out and follow”; “that I
strongly influenced others’ beliefs and behaviour”
In addition, we also assessed self-esteem with the items “quite satisfied with myself,”
“that I had many positive qualities,” and “a strong sense of self-respect” (adapted from
Rosenberg Self-Esteem Scale). Finally, we also measured pleasant (“joyful,”
“energized,” “calm,” “content”) and unpleasant (“angry, “sad,” “dejected,” “stressed,”
“frustrated”) affect.
Facebook Measures. At the start of the study (i.e., day 1), participants authorized
our custom application allowing us to download their Facebook status updates (i.e.,
messages they write publically on their profile), as well as the comments made by the
participants’ friends (whose identities were not recorded), during the study period of 2
weeks, in addition to a 2-week period prior to the start of the study. Downloading the
status updates from the 2-week period prior to the start of the study allowed us the
possibility of a manipulation check as well as controlling for individual baseline
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differences. As well, each status updates’ total number of “Likes” and Comments were
downloaded.
Coders read a transcript of each participant’s status updates and rated it on
specific dimensions. A total of three coders were asked to rate the degree to which they
thought the participants’ status updates expressed positivity, as well as the degree to
which they thought the participants’ friends expressed positivity when commenting on
the participants’ status updates. In addition, coders were also asked to rate the likability
of the participants (e.g., “How much do you like this person?”). The ratings were made
for three separate time periods: 1) pre-study, 2) daily, 3) overall during-study. All ratings
were made on a 7-point Likert scale (1 = not at all, 7 = a great deal). Coders were asked
to leave blank any items they felt they could not assess (e.g., positivity/negativity of
friends when friends did not leave any messages). All coders were blind to the study’s
hypotheses and to the participants’ condition and self-esteem.
Procedure
Participants who met the inclusion criteria were contacted by email to participate
in an online study lasting 2 weeks. They were told that the study was examining how
people with different personality types use online social networks. Upon consenting to
the study, participants were asked to authorize a custom Facebook application that
allowed the experimenters to download the participants’ status updates up to 2 weeks
before the study began. Participants then completed a set of online questionnaires that
include the Rosenberg (1965) Self-Esteem Scale, in addition to the daily measures
including autonomy, competence, relatedness, self-actualization, security, popularity, and
pleasant and unpleasant affect.
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After completing the daily measures, participants were reminded to complete an
additional task which constituted the manipulation. Depending on the condition,
participants received the following instructions: In the experimental condition,
participants were asked “Please remember to post something positive on Facebook (e.g.,
something that happened to you or others, the weather, etc.) before the end of the day;” in
the control condition participants were asked “Please write something positive (e.g.
something positive that happened to you or others, the weather, etc.) in the box below;”
and finally, in the base condition participants were asked “Please remember to post
something on Facebook (e.g., something that happened to you or others, the weather,
etc.) before the end of the day.”
On the last day of the 2-week study period, participants were again asked to
complete the same online questionnaires as the start of the study (i.e., measuring selfesteem), including the daily measures, as well as demographic information (i.e., age and
gender).
Results
Regression Analyses
The following analyses were hierarchical linear regressions with two dummycoded condition variables (experimental = 0, 0; control = 0, 1; base = 1, 0) and meancentered pre-test self-esteem entered as predictors at Step 1, and the Self-Esteem ×
Condition interactions entered on Step 2. We first examined whether there were indeed
post-test self-esteem improvements due to our experimental manipulation. The results of
our regression revealed that, contrary to our prediction, self-esteem and condition did not
interact to predict post-test self-esteem after 2 weeks, nor was there a significant main
13
effect of conditions, ts < 1.1; unsurprisingly, pre-test self-esteem was positively
associated with post-test self-esteem,β= .86, t(33) = 7.448, p < .001. Failing to confirm
our initial hypothesis, we used the same regression model to predict the total number of
Facebook Likes and Comments the participant received during the study. Self-esteem did
not interact with condition to predict Facebook Likes nor Comments and again there were
no main effects of SE or condition, ts < 1.1.
Since we were unable to confirm our main hypotheses, we conducted further
analyses by examining the 6 psychological needs across the start of the study and the end
of the study. The autonomy (r = .90), competence (r = .82), relatedness (α = .88), selfactualization (r = .79), security (r = .62), and popularity (r = .80) items were averaged to
form their respective composites. The composites were calculated for each day of the
study and then averaged across the entire study. Upon closer examination, popularity and
relatedness seemed to measure similar constructs: average feelings of popularity and
average feelings of relatedness were strongly correlated (r = .60). Therefore, the two
scores were combined to form a social relatedness composite.
If neither pre-test self-esteem nor our manipulation predicted post-test self-esteem
as expected, we wondered whether these variables would predict feelings of social
relatedness. Unsurprisingly, we discovered that pre-test self-esteem was positively
associated with feelings of social relatedness, β= .61, t(33) = 2.764, p = .008, such that
those with higher pre-test self-esteem felt more social relatedness than did those with
lower pre-test self-esteem, but there was no interaction between SE and condition, t < 1.1.
There also were no effects on the other social needs indicators.
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As our manipulation and SE did not interact to affect the outcome of our
dependent variables of interest,we were interested in whether participants’ friends’
feedback were related instead. We suspected that total number of Facebook Likes and
Comments would be positively associated, since users who choose to comment may also
choose to like the status updates as well. Indeed, total Likes and Comments were highly
correlated (r = .55), so we standardized the total number of Facebook Likes and
Comments and combined them to form a Facebook Feedback score.
To examine whether our manipulation interacted with Facebook Feedback to
affect participants’ self-esteem, we used a hierarchical linear regression model with
condition and Facebook Feedback entered as predictors at Step 1, while controlling for
pre-test self-esteem, and the Facebook Feedback × Condition interaction entered at Step
2. Again, we did not find the expected interaction nor an effect of condition. However,
we did find a marginal effect of Facebook Feedback, such that as it increased so did postmeasured self-esteem, β= .269, t(33) = -2.07, p = .095.
We were then interested in whether Facebook Feedback would affect participants’
feelings of pleasant or unpleasant affects. We expected that participants high in Facebook
Feedback would feel more pleasant affect and less unpleasant affect, while those low in
Facebook Feedback should feel less pleasant affect and more unpleasant affect. The
regression analyses did not support our prediction: there were no interactions or main
effects of Facebook Feedback and condition to predict feelings of pleasant or unpleasant
affects, ts < 1.
Similarly, we wanted to investigate whether Facebook Feedback would affect
participants’ feelings of social relatedness: we predicted that participants high in
15
Facebook Feedback would feel more social relatedness than those low in Facebook
Feedback, especially in the experimental condition. Using the same regression model, we
found that although Facebook Feedback did not interact with our manipulation to predict
feelings of social relatedness, participants high in Facebook Feedback felt more social
relatedness than did those low in Facebook Feedback, β= .44, t(33) = -2.603, p = .014.
Also, there was a main effect of condition, β= -.749, t(33) = -2.07, p = .047, such that
participants in the base condition felt lower social relatedness than did those in the
control and experimental conditions. In either condition involving making positive
statements, then, people reported higher social relatedness than in the condition with no
instructions to make positive statements.
Although we did not find that low self-esteem people would benefit more greatly
from Facebook Feedback as we predicted, then, we did indeed support the prediction that
Facebook Feedback would improve one’s feelings of social relatedness—a key
component for self-esteem according to Sociometer Theory. However, we were then also
interested in whether self-esteem would play a role in how participants’ are perceived by
others. In order to investigate this, we averaged our coders’ ratings of participants’
positivity (α = .73), participants’ friends’ positivity (α = .64), and participants’ likability
(α = .69) based on the participants’ Facebook transcripts to create their respective scores.
First, we examined whether participants in the experimental condition would be
rated more “positive” than in the base condition or the control condition. Using our first
regression model, with pre-test self-esteem and condition entered as predictors, we found
a Self-Esteem × Condition interaction to predict participants’ positivity, β= 1.143, t(33)
= -2.208, p = .036. Participants with low self-esteem were seen as more positive than
16
those with high self-esteem in the experimental condition, β= -1.077, t(33) = -2.273, p =
.031, but there were no effects of self-esteem in either the base or control conditions, ts <
1. In addition, participants with low self-esteem in the experimental condition were seen
as more positive than those in the base or control conditions, β= -1.734, t(33) = -2.166, p
= .040, while there were no differences between conditions among participants with high
self-esteem, β= 1.25, t(33) = 1.57, p = .128. This suggests that low self-esteem
participants were “better” at being positive than anyone else in any other conditions, even
when compared to those with high self-esteem in the same condition (Figure 1).
With the previous finding in mind, we wondered if this resulted in participants’
friends being more positive as well, in response. Our analyses revealed precisely that.
Again using the same regression model, we found that indeed participants’ self-esteem
interacted with condition to predict friends’ positivity, β= 1.195, t(33) = 2.169, p = .039,
such that, in the experimental condition, low self-esteem participants’ friends were seen
as more positive than high self-esteem participants’ friends, β= -1.158, t(33) = -2.295, p
= .030; there were no effects of self-esteem in the other two conditions, ts < 1. Again,
low self-esteem participants’ friends were seen as more positive in the experimental
condition than in the base or control conditions,β= -2.067, t(33) = -2.424, p = .023.
Interestingly, high self-esteem participants’ friends were seen as marginally less positive
in the experimental condition compared to the other two conditions, β= 1.493, t(33) =
1.771, p = .088.
Finally, we wanted to examine which participants would be viewed as more
likable by our coders. Our regression model revealed a Self-Esteem × Condition
interaction to predict participants’ ratings of likability, β= 1.284, t(33) = 2.223, p = .035.
17
We found that in the experimental condition, but not in the base or control conditions,
participants with low self-esteem were rated more likable than those with high selfesteem, β= -1.098, t(33) = -2.078, p = .047. Moreover, low self-esteem participants were
rated more likable in the experimental condition compared to low self-esteem participants
in the base or control conditions,β= -2.355, t(33) = -2.814, p = .009, while there were no
effects of condition among participants with high self-esteem.
Regression analyses revealed some important effects of experimental condition
and premeasured self-esteem, although not all of our key hypotheses garnered support. It
is important to recognize that the sample size was very small for these kinds of mostly
between-subjects analyses, and so although it seemed worthwhile to explore the reported
findings fully they must be considered cautiously. In the analyses that follow, we used
hierarchical linear modeling (HLM) techniques to investigate whether Facebook
Feedback and our manipulation had an overall effect on a daily basis, which examines
dozens of repeated measurements rather than merely comparing the start and end of the
study between groups.
Multilevel Modeling Analyses
The following analyses were conducted with data structured such that daily
observations (i.e., daily reports of needs satisfaction, self-esteem, and pleasant or
unpleasant affect) were treated as nested within people at level 1, and people nested
within experimental condition (two dummy-coded variables: experimental = 0, 0; control
= 0, 1; base = 1, 0) at level 2:
Level 1:
𝑦𝑖𝑗 = 𝛽0𝑗 + 𝛽1𝑗 (𝐹𝑒𝑒𝑑𝑏𝑎𝑐𝑘𝑖𝑗 ) + 𝑟𝑖𝑗
18
Level 2:
𝛽0𝑗 = 𝛾00 + 𝛾01 (𝐶𝑜𝑛𝑑𝑖𝑡𝑖𝑜𝑛1𝑗 ) + 𝛾02 (𝐶𝑜𝑛𝑑𝑖𝑡𝑖𝑜𝑛2𝑗 ) + 𝑢0𝑗
𝛽1𝑗 = 𝛾10 + 𝑢1𝑗
At Level 1, daily reports of social relatedness or self-esteem (𝑦𝑖𝑗 ) on day i for
person j is a function of 𝛽0𝑗 , the individual’s intercept, and 𝛽1𝑗 , the individual’s slope
representing the association between the amount of Facebook Feedback he or she
received and his or her feelings of social relatedness or self-esteem. 𝐹𝑒𝑒𝑑𝑏𝑎𝑐𝑘𝑖𝑗 is the
amount of Facebook Feedback the individual received on day i for person j and finally 𝑟𝑖𝑗
is the within-person error. At Level 2, 𝛽0𝑗 is a function of between-persons intercept 𝛾00,
and the effect of the between-persons variables 𝛾01 and 𝛾02 for the condition variables
Condition1 and Condition2. We were interested in whether increases in Facebook
Feedback (𝛽1𝑗 ) would coincide with increases with daily social relatedness and/or selfesteem (𝑦𝑖𝑗 ), and whether this was dependent on condition (𝛾01 and 𝛾02 ). Specifically,
we expected that participants in the experimental condition would experience greater
increases in feelings of social relatedness than in the base or control conditions.
Therefore, our final model was:
𝑦𝑖𝑗 = 𝛾00 + 𝛾01 (𝐶𝑜𝑛𝑑𝑖𝑡𝑖𝑜𝑛1𝑗 ) + 𝛾02 (𝐶𝑜𝑛𝑑𝑖𝑡𝑖𝑜𝑛2𝑗 ) + 𝛾10 (𝐹𝑒𝑒𝑑𝑏𝑎𝑐𝑘)
+ 𝛾11 (𝐶𝑜𝑛𝑑𝑖𝑡𝑖𝑜𝑛1𝑗 ∗ 𝐹𝑒𝑒𝑑𝑏𝑎𝑐𝑘𝑖𝑗 ) + 𝛾12 (𝐶𝑜𝑛𝑑𝑖𝑡𝑖𝑜𝑛2𝑗 ∗ 𝐹𝑒𝑒𝑑𝑏𝑎𝑐𝑘𝑖𝑗 )
+ 𝑢0𝑗 + 𝑢1𝑗 + 𝑟𝑖𝑗
The slopes, 𝛾11 and 𝛾12, represent the cross-level interactions. Since participants’
were less likely to receive Comments (M = 4.12, SD = 6.1) on their status updates than
Likes on any given day (M = 7.48, SD = 7.9), and indeed there were many instances of
zero comments, we chose to use Facebook Likes as our Feedback variable. In addition,
we organized the data such that we examined the changes in our dependent variables
19
from previous days. All dependent variables were grand mean centered according to
guidelines offered by Nezlek (2001).
The results from these analyses are displayed in Table 1, as well as being
displayed graphically to aid in description. As shown, pleasant affect was not a function
Facebook Likes or Condition, nor was there an interaction. We did find, however, that an
increase in Facebook Likes resulted in a lessening in feelings of unpleasant affect (Figure
2).
Interestingly, we also found a Likes × Condition interaction when predicting
changes in daily self-esteem. As shown in Figure 3, it appears that participants in the
experimental and control conditions had lower self-esteem when they received fewer
likes when compared to those who received fewer likes in the base condition. Moreover,
those in the experimental and control conditions appears to feel higher self-esteem when
they received more likes when compared to those who received more likes in the base
condition.
A similar pattern can be seen with feelings of social relatedness (Figure 4), such
that those in the experimental and control conditions, compared to those in the base
condition, evidently felt less social relatedness when they received fewer likes. Likewise,
those in the experimental and control conditions felt more social relatedness when they
received more likes, compared to those in the base condition. It appears, then, that
receiving positive feedback from friends is beneficial particularly when the individual
has been positive, and, likewise, receiving no feedback can be particularly detrimental
when making an effort to be positive.
20
Discussion
We investigated the effect of positive feedback and self-esteem on relatedness and
self-esteem change by manipulating people’s communication positivity and medium (i.e.,
Facebook, where they could receive feedback, vs. survey item, where they would not
receive feedback) and examining their state changes in several psychological indices after
2 weeks. We mainly predicted that LSEs being more positive on Facebook would lead to
increased self-esteem over time if peers reaffirm the positivity. Moreover, we also
predicted that self-esteem would be reactive to daily fluctuations of Facebook feedback,
particularly when being positive on Facebook. Although several of our key predictions
were not supported, there were many findings that were broadly consistent with
hypotheses.
Main Findings
First, we wanted to look at whether LSEs posting positive feedback on Facebook
would increase in self-esteem at the end of the study. Our results did not support this
prediction. Second, we were also interested in the components of self-esteem according
to Sociometer Theory—mainly, relatedness needs. Again, pre-test self-esteem did not
interact with our experimental manipulation to predict feelings of social relatedness.
Third, since there was no difference in the amount of Facebook feedback received
between our conditions, we looked at whether Facebook feedback interacted with
condition to predict feelings of social relatedness. Indeed, we found that across
conditions, an increase in Facebook feedback led to an increase in feelings of social
relatedness. Finally, we wanted to see how others perceived the participants. Based on
observer ratings, our results indicated that LSEs in particular were very good at being
21
positive on Facebook and thus resulted in receiving more positive feedback from their
friends and were seen as more likable.
Although we did not find an increase in post-test self-esteem, we did find
components that are vital to building self-esteem, as proposed by Sociometer Theory,
such as feelings of social relatedness, likability, and acceptance (i.e., positive feedback).
It is possible that the duration of our study was not sufficient for producing measurable
changes in self-esteem. Indeed, although our manipulation affected components for
building self-esteem, it may require longer, repeated exposure of these components to
achieve higher self-esteem. However, the results of our regression analyses should be
taken with caution: although some findings were interesting and promising, the low
sample size does not instill confidence in our between-subjects analyses.
We then wanted to look at how daily fluctuations in Facebook feedback received
would affect daily feelings of self-esteem, social relatedness, and pleasant and unpleasant
affect. We expected that an increase in Facebook feedback, particularly in the
experimental condition, would result in an increase in feelings of self-esteem, social
relatedness, and pleasant affect, and a decrease in unpleasant affect. Our HLM analyses
showed that having more Facebook likes does indeed decrease participants’ unpleasant
affect. Less intuitively, however, likes did not seem to increase participants’ pleasant
affect. Why this is the case is unclear—Buckley, Winkel and Leary (2003) found that
people led to feel rejection felt the least positive (or pleasant) and most negative (or
unpleasant) affect. However, positive and negative affects have long been considered
independent (see Diener & Emmons, 1984; Russel & Carroll, 1999; Naragon & Watson,
2009) and may be responsive to different stimuli.
22
We found an interaction between daily feedback and our experimental condition
on several outcome variables. However, it seems that it does not matter whether one has
been positive on Facebook or on a survey item: being positive at all seems to increase
people’s self-esteem when they receive feedback, regardless of whether the medium for
being positive was Facebook or not. While our results showed that receiving Facebook
Feedback affected participants’ daily feelings of social relatedness and self-esteem,
particularly when participants were asked to be positive, it is not readily apparent why
there seems to be no difference in pattern between asking participants to be positive on
Facebook or asking them to be positive on our survey. Perhaps being positive in general
put our participants’ in a state of need or desire for acceptance and therefore they became
sensitive to receiving feedback regardless of whether it was feedback in response to their
positivity. Gardner, Pickett, and Brewer (2000) found that arousing participants’ need to
belong, by inducing feelings of rejection, led to them becoming more attentive to social
information. Similarly, LSEs making positive self-statements led to them having worse
moods and lower self-esteem (Wood et al., 2009). Being positive may have first put some
participants in a state of being more attentive or sensitive to social information (much as
being rejected did, in previous research). Indeed, we found that participants in the “be
positive” conditions did feel less social relatedness and self-esteem when receiving less
likes compared to those in the base condition. It appears that being positive can be
beneficial but only when receiving some reassurance, in this case in the form of
Facebook likes, and can be detrimental when reassurance is not available.
23
Implications
The present research provides evidence that online social networks can be a viable
platform for satisfying social relatedness needs at least to some extent. Likewise, these
findings corroborate the Sociometer Theory of self-esteem, such that an increase in daily
positive social feedback was associated with an increase in self-esteem and relatedness
needs satisfaction.
We were concerned that when attempting to be more positive, people may instead
experience deleterious effects on their self-esteem as had been shown in laboratory
research (Wood et al., 2009). Our results replicated this finding—but only when positive
feedback was absent. This suggests that feedback is a critical component for reaping the
benefits of being positive, and people may need to make a conscious effort to be positive
in general. Although we did not find an effect on post-test self-esteem based on our
manipulation, we expect that being more positive and creating more rewarding social
relationships (Forest & Wood, 2012) would eventually lead to higher self-esteem, per
Sociometer Theory. Consistent and repeated positivity on Facebook may lead LSEs to
higher gains in the long-term than what we found in our present study.
Indeed, our results suggest that LSEs were “better” at being positive than HSEs,
which fits with some other findings—Gould (2009) showed that after being excluded,
children found comfort in chatting online; in addition, LSEs, compared to HSEs, tend to
self-disclose more to online friends than to offline friends, and feel that Facebook is a
safer place to express themselves (Zwyica & Danowski, 2008; Forest & Wood, 2012). It
is possible, then, that LSEs do not realize the importance of being positive when
expressing themselves on Facebook. Indeed, LSEs tend to be more pessimistic and tend
24
to view events as being negative (Rosenberg & Owen, 2001). However, it is important to
note again that while we might wish to encourage LSEs to express more positivity on
Facebook, it may be detrimental if the positivity is inauthentic (Wood et al., 2009). Our
manipulation did not tell participants what to write specifically (e.g., “I love myself”) but
to find something positive to write about (e.g., “I think I did well on my test today”).
Therefore, LSEs might benefit most by being reminded to express positivity more
regularly but only when also being authentic.
Finally, to our knowledge, our research is the first to show one mechanism,
Facebook likes, through which people may partially satisfy their relatedness needs on
online social media. Other researchers have found that emotions can spread through one’s
social network (Kramer et al., 2014). In their study, they manipulated the amount of
positivity or negativity that was shown to individuals and showed that there was a
positive correlation between the change in positivity/negativity shown and the amount of
positivity or negativity that the individual then posted. Using a similar method, we would
expect that manipulating the amount of Facebook likes one receives (or is shown) would
influence one’s attempts to garner more likes.
There were some limitations to the present study with regard to the methodology
and the available data. First, very few participants posted every day of the study as
instructed so the manipulations may not have been as impactful as intended. Second, our
sample size for the study was quite small, particularly in the experimental condition (n =
11), so there likely was not enough statistical power to find our hypothesized effect when
it came to long-term change. Future studies therefore may need to devise a method to
ensure greater probability of task adherence so that we may have a larger and more
25
consistent data set. We may also wish to measure other variables of interest such as
perceived positive feedback from peers, perceived relational value, and self-reported
close friends (and whether their “likes” and comments cause a greater effect than just
acquaintances).
Final Remarks
As the world continues to become more connected to the Internet, people supplant
face-to-face interactions with online ones. As our results suggest, online interactions may
play a role in satisfying social needs. While we have focused on the possibility for
increases in self-esteem and feelings social relatedness, our findings should be considered
also in light of many anecdotal examples of things that can go awry when people rely on
online interactions and indirect social indicators to meet social needs.
Ben Eisenkop, a member of the popular social networking site Reddit, was
recently banned from the site for “vote manipulation”—he used multiple accounts to like
his own posts and content (Knoblauch, 2014). This was notable because he had the
highest “karma,” conceptually equivalent to Facebook likes, among all users of the site.
Despite clearly already receiving the most likes by other users, he still felt the need to
artificially increase his likes by creating other accounts. In his own words, he did it for
“public engagement.” Although we do not know whether Ben Eisenkop has low or high
self-esteem, clearly he attached personal importance to the arguably arbitrary number.
Along the same lines, the short film “What’s on your mind” by Shaun Higton
(2014) depicts a man browsing Facebook and becoming increasingly obsessed with the
number of likes he received. His posts were mostly positive and generally showed
himself enjoying life, which led to receiving more likes. In one example, the man posts
26
about finally quitting his “dead end job.” In reality, however, he was actually fired from
his position, and he can be seen grudgingly leaving the office. In another scene, he is seen
drinking and crying alone in his car, while posting a picture of himself smiling,
seemingly in a dance club. The film ends with the man alone in his apartment on the
verge of tears, finally posting “My life sucks.” On one hand, this film shows the extent to
which one might rely on online social networks in an attempt to satisfy social relatedness
needs. On the other hand, the film also illustrates how being inauthentic can still lead to
detrimental effects (Wood et al., 2009), despite being positive and receiving positive
feedback.
The vicious cycle that people with low self-esteem experience can be devastating.
People with low self-esteem are more likely to take part in higher risk and more
dangerous activities, arguably in an attempt to be accepted (Leary, Schreindorfer, &
Haupt, 1995). Our findings, in combination with other findings in the broader social
psychological literature, elucidates some of the mechanisms involved in maintaining selfesteem: If people with low self-esteem are motivated by social relatedness needs, then it
could be advantageous for them to achieve a sense of belongingness through a safe
medium. New technologies and services, such as Facebook, offer precisely the safe
environment that might help people with low self-esteem foster stronger relationships.
Efforts to improve one’s relationships might be more successful if people with low selfesteem are able to successfully generate positive feedback in social settings.
27
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Table 1. Daily Observations As a Function of Facebook Likes and Condition
Predictor
Intercept
Likes
Condition1
Condition2
Likes*C1
Likes*C2
Social Relatedness
Estimate (se)
t
-1.262 (.096)
-1.312
.024 (.009)
2.774**
.151 (.126)
1.201
.056 (.128)
.436
-.024 (.012)
-1.963*
-.014 (.011)
-1.261
* p < .06, ** p < .05
Self-Esteem
Estimate (se)
t
-.072 (.101)
-.712
.019 (.009)
2.18**
.093 (.132)
.709
-.009 (.134)
-.066
-.026 (.013)
-2.057**
-.006 (.012)
-.515
Pleasant Affect
Estimate (se)
t
-.027 (.137)
-.198
.009 (.014)
.630
.021 (.173)
.123
-.060 (.177)
-.341
-.008 (.018)
-.453
.003 (.016)
.185
Unpleasant Affect
Estimate (se)
t
-.198 (.116)
1.665
.630 (.011)
-2.691**
.123 (.148)
-.969
-.341 (.153)
-.071
-.453 (.015)
1.722
.185 (.014)
.917
34
Figure 1. Coder ratings of participants’ overall positivity across study period according to
Facebook transcripts as a function of experimental condition and self-esteem. Low SE represents
the value 1 SD below the mean; High SE represents the value 1 SD above the mean.
35
Base
Control
Experimental
0.30
Unpleasant Affect
0.20
0.10
0.00
Likes Low
Likes High
-0.10
-0.20
-0.30
-0.40
Figure 2. Daily Ratings of Unpleasant Affect as a function of experimental condition and
number of Facebook Likes. Likes Low represents the value 1 SD below the mean; Likes High
represents the value 1 SD above the mean.
36
Base
Control
Experimental
0.25
0.20
Self-Esteem
0.15
0.10
0.05
0.00
-0.05
Likes Low
Likes High
-0.10
-0.15
Figure 3. Daily Ratings of Self-Esteem as a function of experimental condition and number of
Facebook Likes. Likes Low represents the value 1 SD below the mean; Likes High represents the
value 1 SD above the mean.
37
Base
Control
Experimental
0.30
0.25
Social Relatedness
0.20
0.15
0.10
0.05
0.00
-0.05
Likes Low
Likes High
-0.10
-0.15
-0.20
Figure 4. Daily Ratings of Social Relatedness (composite of popularity and relatedness) as a
function of experimental condition and number of Facebook Likes. Likes Low represents the
value 1 SD below the mean; Likes High represents the value 1 SD above the mean.