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Read the open access Bitter (2016) article Consequences of customer engagement behavior: when negative Facebook posts have positive effects. Briefly address the topics below in a 500-word written assignment. Cite other journal references available in the Reference Article module, or in the PBSC library databases, where appropriate. Use standard APA format, provide proper in-text citations for all references, and place a reference list at the end. Do NOT copy and paste material directly from the articles.
Section I – Use a Level 1 heading: Impact of Social Media Communication on Customer Relations. Discuss how two-way communication on social media channels impacts businesses both positively and negatively. Provide any personal examples from your experience.
Section II – Use a Level 1 heading: Building relationships through positive communication. Based on Bitter’s analysis, demonstrate your skill at building relationships for all customers of an organization. Accomplish this by proposing a strategy that you, an entrepreneur for a new startup, would employ to communicate with customers who post negative comments that harm your business. Explain how your communication efforts would re-engage these customers and encourage their loyalty. Discuss the strengths, weaknesses, and challenges in implementing this effort.
Attachments area

RESEARCH PAPER

Consequences of customer engagement behavior:
when negative Facebook posts have positive effects

Sofie Bitter1 & Sonja Grabner-Kräuter1

Received: 23 March 2015 /Accepted: 11 March 2016 /Published online: 1 April 2016
# The Author(s) 2016. This article is published with open access at Springerlink.com

Abstract Sharing product information has become an inte-
gral part of today’s online social networking world. This re-
search study addresses the effects of customer engagement
behavior in online social networks on other consumers in or-
der to understand how online social connections impact deci-
sion making. We investigate how different variations of a
brand-related Facebook post trigger different response reac-
tions. In particular, we analyze under which conditions nega-
tive posts can have positive consequences. The results of two
online experiments set in a restaurant context suggest a differ-
ence when the user knows the restaurant brand. For users who
are familiar with the restaurant brand, a positive effect of neg-
ative information posted by distant acquaintances is found
with regard to the visiting intention of the user. The results
of both experiments demonstrate that information posted by a
close friend is perceived to be more diagnostic. For users not
familiar with the restaurant brand, negative posts from strong
ties induce the highest diagnosticity levels.

Keywords Social networking sites . Facebook . Customer
engagement behavior . Valence . Tie strength . Diagnosticity

JEL Classification M31 Marketing

Introduction

Online social networking is more popular than ever before and
increasingly impacts consumer purchase decisions. Resulting
in a facilitated access to other consumers’ feedback, the prolif-
eration of social networking sites offers fundamentally new
ways of engagement and interaction among existing as well
as potential consumers and brands (e.g., Hess et al. 2011;
Kabadayi and Price 2014). Nowadays, it is impossible to imag-
ine online life without engaged and active users. Following
this, the concept of customer engagement behavior, defined
by van Doorn et al. as Bcustomer’s behavioral manifestations
that have a brand or firm focus, beyond purchase, resulting
from motivational drivers^ (2010, p. 254), has become an issue
that is currently the focus of much attention and activity.

For both marketers and academics, it is of interest to
understand the consequences of customer engagement in
online social networks (OSNs). Nonetheless, there is a pau-
city of scholarly research related to a coherent understand-
ing of how social connections in OSNs impact decision
making (Takac et al. 2011). In other words, little is known
about Bthe relationship between customer behavioral en-
gagement and other proximal constructs^ (Gummerus
et al. 2012, p. 858); for example, to what extent the forma-
tion of consumer attitudes is driven by specific consumer
Bengagement^ cognitions, emotions and behaviors, or what
effects on consumer purchase intentions can be expected
(Hollebeek and Chen 2014). This illustrates the need to
examine the outcomes that result from customers’ brand-
related interactions in OSNs. Besides, the majority of
pioneering research has tended to focus on positively
valenced customer engagement and thus has largely
overlooked potential negatively valenced manifestations of
this emerging concept and their implications for (other) con-
sumers and business firms (Hollebeek and Chen 2014).

Responsible Editors: Ulrike Baumöl and Linda Hollebeek

Sofie Bitter and Sonja Grabner-Kräuter contributed equally to this work.

* Sofie Bitter
[email protected]; [email protected]

1 Universitätsstrasse 65-67, 9020 Klagenfurt, Austria

Electron Markets (2016) 26:219–231
DOI 10.1007/s12525-016-0220-7

http://crossmark.crossref.org/dialog/?doi=10.1007/s12525-016-0220-7&domain=pdf

This study seeks to address this void by examining poten-
tial effects of both positively and negatively valenced behav-
ioral manifestations of customer engagement on Facebook.
The interest in Facebook is motivated by the undeniable pop-
ularity of the platform – Facebook is the largest and most
widely used social networking site in the world, connecting
over 1.39 billion monthly active users (Facebook 2015) and
hosting over 50 million brand pages (Facebook 2013).
Naturally, one could argue that positive brand-related
Facebook posts trigger positive impressions and negative
posts result in negative impressions. Contrary to this intuitive
expectation and building on previous research (e.g., Berger
et al. 2010; Ein-Gar et al. 2012; Hamilton et al. 2014), we
suggest that, under certain conditions, a small piece of nega-
tive information, such as a negative Facebook comment,
might affect the product evaluation in a positive way.

Previous studies have shown that the consequences of
product-related information and recommendations as a behav-
ioral expression of customer engagement can differ, depend-
ing on whether the information source is a close friend (i.e. a
strong tie) or a distant acquaintance (i.e. a weak tie) (e.g.,
Bansal and Voyer 2000; Sen and Lerman 2007; Steffes and
Burgee 2009; Wang and Chang 2013). Drawing on these find-
ings, we investigate the moderating role of tie strength on the
impact of comment valence on purchase decision making. An
experimental design in a restaurant brand context was set up in
order to demonstrate the differential impact of different varia-
tions of a brand-related Facebook comment as particular be-
havioral manifestation of customer engagement. Our investi-
gation was guided by the following research questions:

RQ 1: Are conditions observable that induce positive effects
from negatively valenced customer engagement be-
havior on Facebook?

RQ 2: If so, under which conditions can negatively valenced
customer engagement behavior on Facebook have
positive consequences for brand evaluation and infor-
mation diagnosticity?

RQ 3: What influence on brand evaluation and information
diagnosticity can be expected from positively vs. neg-
atively valenced customer engagement behavior that
is performed by either a close friend or a distant
acquaintance?

To address these research questions, we analyze how neg-
atively valenced as distinct from positively valenced brand-
related information from a close as distinct from a distant
Facebook friend influences the consumer’s visiting intention
and the Facebook post’s perceived diagnosticity. Referring to
the Bblemishing effect^ described by (Ein-Gar et al. 2012) we
first examine if a negatively valenced brand-related Facebook
comment from a distant friend can induce a positive effect on
brand evaluation. We expect a positive effect of such a minor

piece of negative information on visiting intentions only in a
situation when users are familiar with the restaurant brand and
have a positive attitude towards it, since a positive attitude
towards the brand is a precondition for the blemishing effect
to occur. We also examine the impact of the different varia-
tions of the Facebook post on perceived diagnosticity, which
can be described as the degree to which the consumer believes
the information they receive is useful in evaluating the brand’s
attributes (see e.g. Kempf and Smith 1998). Due to the nega-
tivity bias in information diagnosticity (e.g., Herr et al. 1991;
Mizerski 1982), negatively valenced posts can be expected to
be perceived as more diagnostic and useful for the evaluation
of the restaurant brand than positively valenced comments. In
a situation when users are unfamiliar with the restaurant
brand, the expected Bpositive effect^ of a negative Facebook
comment should still manifest itself in its higher perceived
diagnosticity, as suggested by the negativity bias.
Additionally, the effect should be stronger for negative com-
ments from close friends. In the remainder of this paper, we
briefly review the literature and suggest a conceptual frame-
work for hypothesis development that links Service-Dominant
(S-D) logic with the concept of tie strength from social net-
work theory. Next, we report on two experimental studies
analyzing Facebook users’ reactions to manipulated
Facebook posts to test our hypotheses. The paper closes with
theoretical and managerial implications, limitations and future
research directions.

Literature review and hypotheses development

Customer engagement behavior and its consequences

During the past decade, the concept of customer engagement
has received increasing attention from both marketing practi-
tioners and researchers. The Marketing Science Institute has
identified Bcustomer engagement^ as a key research area con-
tributing to an improved understanding of consumer behavior
in complex, interactive and/or co-creative environments
(Marketing Science Institute 2010). Meanwhile, the theoreti-
cal meaning and foundations of the customer engagement
concept have been established in the marketing and service
literature (Brodie et al. 2011; Hollebeek and Chen 2014;
Vivek et al. 2012). However, to date, there is still a relative
deficit in empirical studies on customer engagement in general
and even fewer exist on customer engagement in social media
(e.g., Bitter et al. 2014; Gummerus et al. 2012; Hollebeek and
Chen 2014).

Origins of engagement-based concepts such as Bbrand
engagement^ or Bcustomer engagement^ can be traced to var-
ious academic disciplines including psychology, sociology and
organizational behavior (Brodie et al. 2011; Vivek et al. 2012).
Brodie et al. (2011) provide a comprehensive conceptual

220 S. Bitter, S. Grabner-Kräuter

analysis of customer engagement in the marketing and service
literature and suggest that its conceptual roots can best be ex-
plained by drawing on theoretical approaches that address in-
teractive experience and value co-creation within marketing
relationships. From this perspective, consumers are not viewed
primarily as passive recipients of marketing cues but rather as
proactive participants in interactive, value-generating co-crea-
tion processes (Hollebeek 2013; Sawhney et al. 2005; Vargo
and Lusch 2004, 2008). Accordingly, the theoretical founda-
tions of the customer engagement concept are established in
the expanded domain of relationship marketing, and the S-D
logic (Brodie et al. 2011; Vivek et al. 2012). Brodie et al.
(2011) point out that specific fundamental propositions under-
lying the S-D logic are of particular relevance for substantiat-
ing the customer engagement concept. This reflects customers’
interactive, co-creative activities and experiences with other
stakeholders in focal, networked service relationships (for a
detailed explanation see Brodie et al. 2011).

Several definitions of customer engagement have been pro-
posed in the marketing and service literature (see the overview
e.g. in Hollebeek 2013). The majority of definitions adopt a
multidimensional view of engagement, whereby three-
dimensional (i.e., cognitive, emotional and behavioral) cus-
tomer engagement concepts have been suggested in the liter-
ature most often (Brodie et al. 2011). Obviously, the concept
of customer engagement behavior (CEB) refers to the behav-
ioral dimension of customer engagement. The specific expres-
sions of the cognitive, emotional and behavioral dimension
may vary across different engagement-based concepts and
contexts (Hollebeek 2013; Vivek et al. 2012). With the advent
of Web 2.0 technologies and applications, particularly the
number of behavioral engagement options for customers has
grown dramatically (van Doorn et al. 2010), requiring specific
research efforts. Hence, in this paper, we focus on behavioral
manifestations of customer engagement on social networking
sites.

From a managerial perspective, B[m]any CEBs such as re-
ferral behaviors, [word-of-mouth] WOM behaviors, and ac-
tions aimed at generating and disseminating information (e.g.,
blogging) should affect purchase behavior of focal as well as
other customers and consequently customer equity^ (van
Doorn et al. 2010, p. 259). Previous empirical studies on the
consequences of customer engagement found that, to some
extent, growing customer engagement generates greater cus-
tomer value increases for hedonic than for utilitarian brands
(Hollebeek 2012). Wei et al. (2013) concentrate on one partic-
ular type of customer engagement behavior, namely on user-
generated hotel reviews and analyze potential customers’ per-
ceptions of CEB and hotels’ management responses to CEB.
Gummerus et al. (2012) examine the effect of customer en-
gagement behaviors on perceived relationship benefits and
relationship outcomes. Jahn and Kunz (2012) focus on
Facebook fan page participation and its impact on the

customer brand relationship. A study by Pan and Chiou
(2011) tests the effects of strong vs. weak social relationships
and positive vs. negative messages on perceived trust of online
information in a discussion forum. However, empirical studies
on the consequences of brand-related comments by Facebook
users as a specific manifestation of CEB remain scarce.

As mentioned above, CEB on social networking sites can
find its expression through positive (e.g., posting a liking
comment on a brand community site) or negative actions
(e.g., posting a negative brand message on Facebook) (e.g.,
Brodie et al. 2011; Hollebeek and Chen 2014; van Doorn et al.
2010). In any case, the importance of negative behavior
should not be ignored. Previous research in an electronic
word-of-mouth (for a conceptual definition of eWOM and a
systematic review of eWOM research see e.g. Cheung and
Thadani 2012) and online review context shows that negative
comments have stronger effects on purchase decisions, in con-
trast to positive electronic word-of-mouth (Chang and Wu
2014; Lee et al. 2008). It is suggested Bthat unfavorable infor-
mation is somehow more shocking or surprising, and there-
fore has more influence on forming evaluations^. (Mizerski
1982, p. 302). However, as Hollebeek and Chen (2014) point
out as a result of a comprehensive literature review, the ma-
jority of research has focused on positively valenced expres-
sions of customer and/or brand engagement and thus has
neglected negatively valenced manifestations of customer en-
gagement. Therefore, this research study considers both vari-
ations of message valence, positive and negative, to investi-
gate how Facebook users’ brand-related comments affect vis-
iting intentions with regard to a restaurant.

Intuitively, one would assume that positive brand-related
comments lead to higher visiting intentions and negative
brand-related comments lead to lower visiting intentions.
In contrast to this intuition, research has shown that weak
negative information might sometimes enhance the evalua-
tion of an object (Ein-Gar et al. 2012). In their seminal study
Lord et al. (1979) found that when people already have a
positive attitude toward an object or issue and receive con-
tradictory arguments this can polarize or intensify their pos-
itive attitude, because people discount the contradictory in-
formation and reinforce the initial information that lead to
the original attitude. Another study on the positive effects of
negative publicity (Berger et al. 2010) indicates that not all
negative word-of-mouth should be quieted, because in some
instances it can actually have positive effects. In a series of
elaborate studies, Ein-Gar et al. (2012) found that in situa-
tions of low processing effort a small dose of negative in-
formation that follows positive information appears to en-
hance consumers’ overall evaluations of the product. They
refer to this as the positive effect of negative information —
weak negative information that merely blemishes a target
can actually enhance its impression under specific conditions
(blemishing effect) (Ein-Gar et al. 2012).

Consequences of customer engagement behavior on Facebook 221

We suggest that a product- or brand-related comment in an
online social network might sometimes represent such a minor
piece of conflicting information, which could accentuate rath-
er than attenuate an initial positive impression. In a situation
when processing effort is low, a negative Facebook post could
prompt a reevaluation of the product or brand and trigger
bolstering processes (Ein-Gar et al. 2012) that lead to a higher
purchase (or visiting) intention than a positive post. However,
we assume that the potentially positive effect of negative
brand-related information on a social networking site such as
Facebook depends on whether or not the user knows the prod-
uct in question and on her/his prior (positive) brand attitude.
Beyond that, we suggest that this effect might interact with
context factors that can have an influence on the information
processing effort of the user. Specifically, we expect a moder-
ating effect of the type of Facebook friend who posts the
comment.

The role of tie strength

Linking S-D logic with concepts from social network theory
offers a complementary understanding to better explain pro-
cesses of resource access and exchange (Laud et al. 2015).
The central premise underlying social network theory is that
actors such as business firms and customers are embedded in
networks of interconnected social relationships (i.e. Bties^)
that provide opportunities for and constraints on behavior
(Brass et al. 2004; Burt 1997).

From a social network perspective, OSNs can be viewed as
a mix of social connections or ties, through which network
members obtain access to the resources of other actors (Tsai
and Ghoshal 1998). It is indeed the sociality factor of OSNs,
which motivates users to adopt them, ultimately impacting
users’ social capital (Chang and Zhu 2012; Grabner-Kräuter
and Bitter 2015). In online social networks, users are usually
connected by both strong and weak ties (DeAndrea et al.
2012; Wang and Chang 2013). Granovetter (1973, p. 1361)
refers to tie strength as the Bcombination of the amount of
time, the emotional intensity, the intimacy (mutual confiding),
and the reciprocal services which characterize the tie^. As
weak ties usually connect individuals from otherwise diverse
groups, they are more likely to provide access to more hetero-
geneous, novel and diverse information compared to strong
ties (Levin et al. 2002).

In an OSN context, weak ties are considered in a relational
way, i.e., they connect acquaintances who do not frequently
interact and, therefore, might not strongly influence each an-
other. Tie strength also has a considerable impact on informa-
tion processing (Chandler and Wieland 2010). The marketing
and sociology literature (e.g., Rindfleisch and Moorman 2001;
Uzzi 1996) suggests that stronger ties generate a richer infor-
mation exchange. Accordingly, it can be assumed that infor-
mation provided by a strong tie is processed with higher effort

compared to information from a weak tie. When a Facebook
user reads a product- or brand-related comment from a strong
tie, her/his information processing effort might be higher and
the product evaluation tends to be based on a fuller consider-
ation of all relevant information, meaning that a negatively
valenced post from a strong tie should result in a more nega-
tive product evaluation, compared to a strong tie’s positively
valenced post. On the other hand, we expect that information
from a weak tie induces a lower processing effort level, which
then facilitates the blemishing effect by referring individuals
back to their initial attitude (Ein-Gar et al. 2012). In this case,
the user’s initial attitude towards the object will be of central
concern (Herr et al. 1991) and a minor piece of conflicting
information in a Facebook post from a weak tie might poten-
tially enhance the overall evaluation of the product or brand
and lead to a positive response behavior towards the negative
message. Visit or purchase intention is an effectiveness mea-
sure that is highly related to product evaluation and frequently
used to anticipate a response behavior to advertising messages
(Daugherty et al. 2008). Hence, we assume:

H1: Tie strength moderates the impact of information va-
lence. More specifically, negatively valenced comments
from a weak tie have a positive effect on purchase or
visiting intentions, if the reader knows the product and
has a positive attitude towards it.

There is sufficient evidence that tie strength influences con-
sumers’ decision making processes in different situations. In a
word-of-mouth context, information from strong ties has been
found to be perceived by receivers as more influential in de-
cision making than information from weak ties (Bansal and
Voyer 2000; Brown and Reingen 1987; East et al. 2008). De
Bruyn and Lilien (2008) observed that tie strength had a pos-
itive effect on awareness during the decision making process
and triggered the recipients’ interest afterwards. In a more
recent study, Wang and Chang (2013) examine the effects of
information valence and tie strength on selected mediating
constructs and on purchase intentions. They found that prod-
uct information and recommendations on Facebook from
close friends are seen as more valuable, trusted and useful,
and facilitate product evaluation compared to information
from distant acquaintances or, to put it another way, that in-
formation provided by strong ties is perceived as having a
high level of diagnosticity, which further increases purchase
intention (Wang and Chang 2013). In this study, we also focus
on the concept of perceived diagnosticity, which reflects the
degree to which consumers consider particular brand-related
comments by other consumers as helpful for evaluating prod-
ucts (Mudambi and Schuff 2010; Wang and Chang 2013).
Accordingly, we posit that brand-related comments provided
by strong-tie sources have a higher perceived diagnosticity
than information provided by weak tie sources.

222 S. Bitter, S. Grabner-Kräuter

H2: The perceived diagnosticity of a brand-related comment
is higher, if the source of information is a strong tie.

In their study, Wang and Chang (2013) focus only on pos-
itive Facebook posts and do not investigate the effects of neg-
ative information and recommendations. However, negatively
valenced information has been found to be more diagnostic
and influential than positively valenced information in the
context of product judgments (Chevalier and Mayzlin 2006;
Hamilton et al. 2014; Herr et al. 1991; Park and Lee 2009).
These findings suggest a negativity bias in processing infor-
mation, whereby negative information has a stronger impact
on judgment and decision making than objectively equivalent
positive information (Sen and Lerman 2007; Skowronski and
Carlston 1989). The negativity bias argues that negative infor-
mation is more diagnostic and useful for product evaluation,
because negative product attributes are considered to be dis-
tinctive of low quality products, whereas positive product at-
tributes are believed to be characteristic of both low and high
quality products (Herr et al. 1991; Willemsen et al. 2011).
Willemsen et al. (2011) found that the negativity effect is more
pronounced for experience goods such as recreational services
and restaurants, because their attributes are intangible.
Therefore, performance evaluations can be verified only by
experience or consumption and there is a greater chance of
making an incorrect decision. In light of these arguments and
findings, the following hypothesis is proposed:

H3: Negatively valenced comments about a restaurant brand
induce a higher perceived diagnosticity than positively
valenced posts.

In a noteworthy study, Ahluwalia (2002) questioned
the robustness of the negativity effect in consumer envi-
ronments and argued that it is dependent on the type of
involvement. Specifically, her findings show that the na-
ture of information processing influences the perceived
diagnosticity of information (Ahluwalia 2002).
Consumers tend to perceive negative brand-related infor-
mation as more diagnostic than positive information
when the subject’s involvement motivates critical pro-
cessing. Again, it can be assumed that brand-related
comments from a strong tie elicit more effortful and
critical processing than comments from a weak tie.
Hence, we assume an interaction effect between tie
strength and information valence on perceived
diagnosticity:

H4: Tie strength moderates the impact of information va-
lence on perceived diagnosticity. More specifically, neg-
atively valenced comments have a stronger impact on
perceived diagnosticity if the information source is a
strong tie.

Figure 1 illustrates the hypothesized linkages among the
variables under investigation. In sum, we assume that negative
posts by weak ties induce the Bpositive effect of negative
information^, but only in cases where the user knows the
product and has a prior positive attitude towards it (H1). We
have not included the user’s product knowledge or attitude
towards the restaurant in the conceptual model, because a
prior positive attitude towards the brand is crucial for testing
H1 but not for testing H2 to H4. Additionally, we suggest that
information posted by a strong tie is perceived as more diag-
nostic than information from a weak tie (H2). Further, accord-
ing to the negativity bias, we assume that negatively valenced
posts are perceived as more diagnostic than positively
valenced posts (H3). Finally, we suggest an interaction effect
and argue that negative brand-related information is perceived
more diagnostic when it is posted by a strong tie (H4). We test
the hypothesized effects in two studies. The primary focus of
study 1 is on the positive effect of negative information when
the previous attitude towards the restaurant brand is highly
positive. In study 2, we refocus the perspective and only con-
sider Facebook users who do not know the restaurant chain at
all.

Study 1

The purpose of the first online experiment was to test the
assumption that, under certain conditions, negative informa-
tion can have positive effects on consumers’ response behav-
ior to the negative message. In particular, the focus of this
experiment was on the hypothesized interaction effect of va-
lence and tie strength on visiting intentions, assuming a pos-
itive effect of negative posts from weak ties when the reader
knows the product and has a positive attitude towards it (H1).
Additionally, we test the impact of brand-related information
on the perceived diagnosticity of the post. Specifically, we
investigate whether negative Facebook posts or posts from
strong ties induce higher levels of diagnosticity, addressing
H2 and H3, as well as the proposed interaction effect of va-
lence and tie strength in this context (H4).

Design

To test the proposed hypotheses, we conducted a 2 valence
(positive vs. negative Facebook post) x 2 tie strength (strong
vs. weak ties) between-subjects online experiment with 82
Facebook users. With a careful isolation of the variables under
consideration, the aim was to obtain an experimental design
that allows for estimating the effects of valence and tie
strength. A Facebook comment that described a visit to a
moderately well known restaurant chain was chosen, as it
was deemed to be an appropriate post that might also appear
on Facebook in reality. The chosen restaurant brand had

Consequences of customer engagement behavior on Facebook 223

recently opened its first outlet in the region and had invested
heavily in regional advertising in advance. As the participants’
positive pre-attitude towards the restaurant is of central impor-
tance for the positive effect of negative information to occur,
this experiment focuses only on Facebook users who knew the
restaurant brand. A scenario was created that revealed either a
positive or a negative comment regarding a visit to a restaurant
posted by a close friend or distant acquaintance (reflecting the
different levels of tie strength). The English translations of the
positive and negative Facebook posts are presented below (see
Figs. 2 and 3), the originals were in German.

Procedure

The experiment was conducted online, using EFS Survey
from Questback. The participants were recruited via
Facebook and the link to the online survey was posted on
the Facebook pages of some of the research team members.
Participants were also encouraged to actively forward the link
to their friends. Additionally, graduate students at a mid-sized
Austrian University were invited to participate in the online
experiment. After clicking on the link leading to the online
questionnaire, the participants were informed that the purpose
of the survey was to gain insights into the consequences of
customer engagement behavior on Facebook. To make sure
that only Facebook users fill in the questionnaire, the partici-
pants were first asked if they have a Facebook account,
followed by questions on their Facebook usage behavior. In
order to evaluate the attitude towards the restaurant chain, we
assessed the user’s attitude before the manipulation of the
Facebook post. To minimize priming effects, the user was
confronted with different restaurant chains and had to indicate,
which of the restaurant chains s/he knew and what his/her
attitude towards the restaurant was. Afterwards, participants
were asked to indicate the first name of three very close
friends (strong ties) or the first name of three distant acquain-
tances (weak ties) on Facebook. Participants in the strong tie
condition were briefed that very close friends are those people
they interact most with, and who are very well known and
trusted. Similarly, participants in the weak tie condition …

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