Word-of-Mouth 1
Word-of-Mouth and Interpersonal Communication:
An Organizing Framework and Directions for Future Research
JONAH BERGER*
*Jonah Berger is the Joseph G. Campbell assistant professor of Marketing
(jberger@wharton.upenn.edu) at the Wharton School, University of Pennsylvania, 700 Jon M.
Huntsman Hall, 3730 Walnut Street, Philadelphia, PA 19104. Thanks to Rebecca Greenblatt for
helping to review and organize the material that formed the basis of this review. Zoey Chen,
Sarah Moore, Grant Packard, Christophe Van den Bulte all provided helpful feedback that
greatly improves the manuscript.
Word-of-Mouth 2
CONTRIBUTION STATEMENT
There is currently huge popular interest in word-of-mouth and social media more broadly (e.g.,
Facebook and Twitter). But while quantitative research has demonstrated the causal impact of
word-of-mouth on behavior across a host of domains, less is known about what drives word-ofmouth and why people talk about certain things rather than others. How does the audience people
are communicating with, as well as the channel they are communicating through, affect what
gets shared? And when and why does word-of-mouth have a stronger impact on behavior? This
paper addresses these, and related questions, as it integrates various research perspectives to shed
light on the behavioral drivers of word-of-mouth. It provides an integrative framework to
organize research on the causes and consequences of word-of-mouth and outlines additional
questions that deserve further study
ABSTRACT
People often share opinions and information with others, and such word-of-mouth has an
important impact on what consumers think, eat, buy and do. But what drives word-of-mouth and
why do people talk about certain things rather than others? How does the audience people are
communicating with, as well as the channel they are communicating through, affect what gets
shared? And when and why does word-of-mouth have a stronger impact on behavior? This
paper addresses these, and related questions, as it integrates various research perspectives to shed
light on the behavioral drivers of word-of-mouth. First it provides an integrative framework to
organize research on the causes and consequences of word-of-mouth. Then, after reviewing
extant literature, it discusses additional questions that deserve further study. Taken together, the
Word-of-Mouth 3
paper provides insight into the psychological factors that shape word-of-mouth, as well as the
consequences of these processes for consumer behavior.
Consumers often talk about and share opinions, news, and information with others. They
chitchat about a recent vacation, complain about a bad movie, or rave about a new restaurant.
They gossip about co-workers, discuss important political issues, and debate the latest sports
rumors. New technologies like Facebook, Twitter, and texting have only made it faster and easier
for people to share stories and information with others. There are thousands of blogs, millions of
tweets, and billions of emails written every day.1
Such interpersonal communication can be described as word-of-mouth, or “informal
communications directed at other consumers about the ownership, usage, or characteristics of
particular goods and services or their sellers," (Westbrook 1987, 261).Word-of-mouth includes
product related discussion (e.g., the Nike shoes were really comfortable) as well as the sharing of
product related content (e.g., Nike ads on YouTube). It includes direct recommendations (e.g.,
you’d love this restaurant) as well as mentions (e.g., we went to this restaurant last week). It
includes literal word-of-mouth, or face-to-face discussions, as well as so called “word of mouse,”
in online mentions and reviews.
Word-of-mouth has a huge impact on consumer behavior. Social talk generates over 3.3
billion brand impressions each day (Keller and Libai 2009). It shapes everything from the
movies we watch and the books we read to the websites we visit and the restaurants we patronize
(Chevalier and Mayzlin 2006; Chintagunta, Gopinath, and Venkataraman 2010; Godes and
1
Social media has received lots of attention but word-of-mouth is not a new phenomenon. Interpersonal
communication has existed since the advent of language. Cavemen shared opinions about which animals were easy
to hunt or where to search for food. Social media has made it easier to quickly share with large groups, but in all the
hype people have forgotten how much word-of-mouth actually happens offline. Some estimates suggest that 75% of
word-of-mouth is face-to-face and only 7% is online (Keller and Fay 2009). Consequently, it is important to
consider the drivers and consequences of both online and offline word-of-mouth.
Word-of-Mouth 4
Mayzlin 2009; Trusov, Bucklin, and Pauwels 2009). The consulting firm McKinsey (2010)
suggests that “word-of-mouth is the primary factor behind 20 to 50 percent of all purchasing
decisions” and that “word-of-mouth generates more than twice the sales of paid advertising in
categories as diverse as skincare and mobile phones” (p 8).
But while it is clear that word-of-mouth is frequent, and important, less is known about
the intervening behavioral processes. What do people talk about and why? How does who
people are talking to (e.g., friends vs. acquaintances) shape what they talk about? Does the
channel consumers talk over (e.g., face-to face or online) impact what gets discussed, and if so,
how? Indeed, some have called word-of-mouth “The world’s most effective, yet least understood
marketing strategy” (Misner 1999).
This article addresses these, and related questions, as it integrates various research
perspectives to shed light on the behavioral drivers of word-of-mouth. Though Godes et al.
(2005) discussed issues in the firm’s management of social interactions, no papers have reviewed
the word-of-mouth literature with a more behavioral perspective in mind. First, I provide a
framework to organize research on the causes and consequences of word-of-mouth.2 Then, after
reviewing extant literature related to this framework, I discuss additional open questions that
deserve further study. Taken together, this paper provides insight into the psychological factors
that shape word-of-mouth, as well as the consequences of these processes for consumer behavior.
AN ORGANIZING FRAMEWORK
In 1948, Harold Lasswell asked a question that underlies the key problems of what has
become communications science: Who says what to whom in what channel with what effect?
2
Given potential issues with self-report, I focus on papers that have looked at actual behavior whenever possible.
Word-of-Mouth 5
Numerous models of communication have been proposed since then (e.g., Berlo 1960; Schramm
1954), but the major components have remained similar (Figure 1).
Word-of-Mouth 6
FIGURE 1: Visual Depiction of Key Communication Factors
Message:
What Gets Shared
Effect
Channel
Source
Audience
There is a
1.
2.
3.
4.
5.
Source, or communication sender
Message, or thing that is being communicated
Audience, or person that is receiving the message
Channel, or medium through which the message is being shared
Effect, or consequence of the communication.
This framework is extremely useful in organizing word-of-mouth research. Consumers
don’t just communicate, they communicate about something, like politics or different car brands.
Why do they talk about some things more than others? What goals drive what people talk about?
Consumers also communicate to someone, like friends or neighbors. How does who people are
talking to shape what they talk about? Communication also happens through a particular
communication channel, like over the phone or face-to-face. How does the channel influence
what people communicate? And finally, that communication has consequences, impacting what
Word-of-Mouth 7
the talker, or listener, thinks, does, or buys in the future.3 When does word-of-mouth have a
larger impact on behavior and why?
In this paper, I consider the word-of-mouth message, audience, channel, and effect,
reviewing relevant research and touching on potential directions for future work. While research
has also looked at who is more likely to talk, given space constraints, I focus on the other four
components in greater detail. 4 Most work on word-of-mouth has focused on its effects, or the
impact interpersonal communication has on the person receiving that communication.
Consequently, we turn to this topic to start.
EFFECTS OF WORD-OF-MOUTH
Broadly speaking, word-of-mouth affects consumer behavior through two key routes
(Van den Bulte and Wuyts 2009). The first is awareness. Word-of-mouth can inform people that
a product or behavior exists (and make it more accessible or top-of-mind). This function is
particularly important for new, unknown, or low-risk products and ideas (Godes and Mayzlin
2009).
3
A great deal of work has examined how social networks determine the flow of information and influence (see Van
den Bulte and Wuyts 2009; Watts 2004 for reviews). Different network structures, for example, may speed or
impede diffusion. Given this article’s focus on opportunities for behavioral research, however, I focus on the more
micro-level topic of word-of-mouth.
4
Early adopters, opinion leaders, market mavens and other people who believe that they have more knowledge or
expertise tend to report sharing their opinion more often people (Engel, Kegerreis & Blackwell 1969; Feick and
Price 1987; Katz and Lazersfeld 1955). Personality factors also play a role, as more extraverted and less
conscientiousness people are more likely to forward emails they receive from others (Chiu, Hsieh, Kao, and Lee
2007) and neurotic people post more frequent (and more emotional) Facebook status updates (Buechel and Berger
2012, see Wilson, Gosling, and Graham 2012 for a broader discussion of factors driving Facebook use). Situational
factors also shape who talks. Highly satisfied or dissatisfied customers seem to share more word-of-mouth
(Anderson 1998) and people asked to rate an experience on a 5-pt scale report higher word-of-mouth
intentions compared with those rating on a 100-pt scale (Chen and Godes 2012).
Word-of-Mouth 8
Word-of-mouth can also have a persuasive function. It can change opinions about
whether something is right or worth doing (similar to informational influence, Deutsch and
Gerard 1955), lead people to change their behavior to be liked or avoid being ostracized (similar
to normative social influence, Deutsch and Gerard 1955), and generate competitive concerns
related to status. Word-of-mouth can also impact the social identity consumers’ associate with a
product or behavior, which may, in turn, affect likelihood of purchase or consumption (Berger
and Heath 2007; 2008). All of these more persuasive functions may be particularly important
when the uncertainty is high (i.e., risk reduction).
Research on the effects of word-of-mouth can be broadly divided into two categories:
quantitative research using field data and more behaviorally based experimental laboratory
research.
Quantitative Research on Word-of-Mouth Effects
Across a variety of domains, quantitative research finds that word-of-mouth has a causal
impact on individual behavior (e.g., purchase or new product adoption) and the firm more
broadly (e.g., aggregate sales or financial performance).5 Word of mouth has been shown to
boost sales of books (Chevalier and Mayzlin 2006), bath and beauty products (Moe and Trusov
2011), and restaurants (Godes and Mayzlin 2009) and speed the adoption and diffusion of new
pharmaceutical drugs (Iyengar et al 2010). Other work suggests that word-of-mouth may boost
sales of music (Dhar and Chang 2009), movies (Chintagunta, Gopinath, and Venkataraman 2010;
5
People may tend to behave similarly to their social ties, but in the field it is often unclear whether this correlation is
driven by influence (i.e., one person affecting another’s behavior), homophily (i.e., the fact that people tend to
interact with similar others), or other factors (e.g., interdependent sampling, Denrell and Le Mens 2007). If
someone goes to a movie their friend recommends, did they go because their friend recommended it, or would they
have seen it anyway simply because they like those types of movies in the first place? This is an important issue that
field work often deals with when trying to estimate the impact of word-of-mouth on behavior (see Aral, Muchnik,
and Sundararajan 2009).
Word-of-Mouth 9
Dellarocas, Zhang, and Awad 2007; Duan, Gu, and Whinston 2008; Liu 2006) and video games
(Zhu and Zhang 2010) and increase microfinance loans (Stephen and Galak 2012), television
show viewership (Godes and Mayzlin 2004), and sign-ups to a social network website (Trusov,
Bucklin, and Pauwels 2009). Some data even suggests that negative word-of-mouth may hurt
stock prices (Luo 2009) and stock returns (Luo 2007).
Most studies that have collected word-of-mouth content have focused on online word-ofmouth, in part because it is easier to acquire. Online word-of-mouth includes consumer reviews
and blog posts, and can be decomposed into volume, valence, and variance (Dellarocas and
Narayan 2006; Moe and Trusov 2011). Volume is the number of reviews or posts that a given
item receives, where more postings are usually associated with increased sales. Valence is the
average rating a product receives (e.g., 3.7 out of 5 stars, Dellarocas et al 2007), or the number of
reviews of different types (e.g., 37 1-star reviews, Chevalier and Mayzlin 2006), and more
positive reviews are generally associated with increased sales (though see Berger, Sorensen, and
Rasmussen 2010). Finally, variance is either the statistical variance (Clemons, Gao, and Hitt
2006) or entropy (Godes and Mayzlin 2004) of the reviews.
One interesting question for future research is when and why different online word-ofmouth metrics have a stronger impact on (or are more predictive of) behavior, sales, or other
relevant outcomes. Different papers have found different metrics to be more or less important.
Some papers have found significant effects on both the volume and valence of reviews
(Chevalier and Mayzlin 2006; Dellarocas, et al. 2007). Other papers have found either only
effects of review volume (Duan, et al. 2008; Liu 2006) or review valence (Chintagunta et al.
2010), but not the other. While some of the difference may be due to the specific modeling
framework used, or dependent variable examined, the distinction between awareness and
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persuasion may also be important. Word-of-mouth may be valued or used differently depending
the novelty and risk involved with the thing being adopted (Godes and Mayzlin 2009; Van den
Bulte and Wuyts 2009). For products that are relatively high-risk, or already quite well-known,
the persuasive function of word-of-mouth should be particularly important. Thus valence should
matter: Positive word-of-mouth should increase choice, while negative word-of-mouth may
decrease it. For low-risk or novel products, however, word-of-mouth should also impact
behavior through increasing awareness. Here, volume should matter more than valence, and
even negative word-of-mouth may boost trial (Berger et al. 2010).
Another rich area for behavioral research is the social dynamics of online reviews. Online
review systems are organized in such a way that consumers are likely to see others’ reviews
before they write their own. How does the volume and valence of existing reviews impact
whether (1) consumers write a review and (2) the nature of the review they write? Consumers
might be more (or less) likely to post their opinion if there are few reviews about a product
already, or if their opinion differs from the prevailing view. Similarly, existing reviews might
generate either assimilation or contrast effects. Indeed, social dynamics may be part of the
reasons that the average product rating tends to decrease as more ratings arrive (Godes and Silva
2012; Li and Hitt 2008). Consequently, researchers have pointed out the importance of
considering (and explicitly modeling) how existing reviews impact the arrival of new reviews
(Moe and Trusov 2011; Moe and Schweidel 2012).
Behavioral Research on Word-of-Mouth Effects
Behavioral research on word-of-mouth has focused on when word-of-mouth may have a
Word-of-Mouth 11
larger impact on behavior and why.6
Most of this work has looked at when and how word-of-mouth affects the word-of-mouth
recipient.7 One important factor is characteristics of the word-of-mouth source. People tend to
listen to more to credible sources, or those that are more trustworthy or have more expertise
(Hovland and Weiss 1951; Petty and Wegner 1998; Pornpitakpan 2004). Other important factors
are the strength of the tie (i.e., friends vs. acquaintances, or strong vs. weak ties) and their
similarity to the word-of-mouth recipient. Per dose or instance of word-of-mouth, strong ties
may be more impactful because people tend to trust them more and think they know more about
their tastes and interests (Bakshy, et al. 2012; Brown and Reingen 1987). That said, people have
more weak ties, or acquaintances, so the overall impact of these types of individuals may be
larger (Bakshy, et al. 2012; see Brown and Reingen 1987; Granovetter 1973; Goldenberg, Libai,
and Muller 2001 for related discussions).8 Similarly, word-of-mouth from similar others may
have a more positive effect (Brown and Reingen 1987; Forman, Ghose, and Wiesenfeld 2008;
also see Naylor, Lamberton, and Norton 2011) because people think their tastes are similar
(Brock 1965). That said, word-of-mouth from dissimilar others may have benefits because these
individuals have access to different information (Granovetter 1973) and may be more familiar
with alternative ways of thinking (Burt 2004). Consequently, whether word-of-mouth from
strong or weak ties and similar or dissimilar others is more impactful may depend on the
6
Though it focuses more on responses to persuasive messages in general, rather than word-of-mouth per se, the
huge literature on attitude change (e.g., the elaboration likelihood model) is also relevant to considering when and
why word-of-mouth may affect behavior. Though a comprehensive review of this literature is beyond the scope of
this paper, see Petty, Wheeler, and Tormala 2012 for a recent review.
7
Word-of-mouth also impacts the person who shares it. If the speaker uses a lot of explaining language when
sharing, for example, they will like a positive experience less and a negative experience more, impacting their
likelihood of retelling that information again (Moore 2012). Sharing self-relevant content online (e.g., Facebook
status updates or tweets) can also aid in emotion regulation, helping neurotic individual manage their emotions and
repair wellbeing after negative emotional experiences (Buechel and Berger 2012).
8
Tie strength also impacts how easily it is to learn from word-of-mouth information and whether such information
leads people to make better decisions (Zhang and Godes 2012).
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particular situation. Finally, heavy users seems to have a larger impact on social contagion
(Iyengar et al. 2011), but it is unclear whether this is because they talk more frequently or
because they have higher status and are thus more likely to be listened to (Godes 2011).
Another important factor is the nature of the word-of-mouth itself. Word-of-mouth varies
in its valence: People can recommend a restaurant, say they hated it, or merely mention that they
went there. Recommendations likely have the most positive impact on behavior, but even
mentions should have a positive effect if they increase product awareness or accessibility (see
Lynch and Srull 1982; also see Berger, et al. 2010; Nedungadi 1990; Stigler 1961). In terms of
absolute impact, negative word-of-mouth may have a stronger impact than positive word-ofmouth, in some cases (Basuroy, Chatterjee, and Ravid 2003; Chevalier and Mayzlin 2006; see
Chen and Lurie 2012 for a potential behavioral explanation) and may be more impactful when
the word-of-mouth event happened further in the past (Smith and Schwarz 2012). Word-ofmouth also varies in its intensity or depth: People can talk briefly about an experience or they
can go on at length. Longer or more in-depth word-of-mouth discussions should have a stronger
impact on behavior [though this may be mitigated for online word-of-mouth, see Godes and
Mayzlin (2004), as people may not end up reading an entire post or review]. Along these lines,
face-to-face word-of-mouth may have a stronger impact than online or written word-of-mouth
because it tends to be more engaging and vivid (Herr, Kardes, and Kim 1991).9 Whether the
word-of-mouth is solicited also matters. Solicited advice seems to have a more positive impact
than unsolicited advice (East et al. 2005) and unsolicited recommendations which go against an
individual’s opinion may even lead to reactance and strengthen the initial opinion (Fitzsimons
and Lehmann 2004). Finally, the level of certainty expressed along with an opinion can also have
9
More generally, chatter can evolve over a huge variety of online channels (e.g., Facebook, Twitter, blogs, etc.), and
research might examine which of these channels actually influence sales versus merely predict them.
Word-of-Mouth 13
an effect, with uncertainty actually being beneficial in some cases (Karmarkar and Tormala
2010).
The susceptibility of the word-of-mouth recipient is also important (Watts and Dodds
2007). Just like some people may be more susceptible to catching a cold or a disease (e.g.,
because they have a weaker immune system), some people may be more susceptible to, or prone
to be affected by, social influence (Aral and Walker 2012; Bearden, Netemeyer, and Tell 1989;
Godes 2011). More susceptible individuals, for example, should be more likely to adopt new
products or ideas if they hear about or see others using them. Though relatively little research has
examined this issue, some data suggests that young people are more susceptible (Park and Lessig
1977; Pasupathi 1999) and people who perceive themselves as opinion leaders are less
susceptible (Iyengar et al. 2011). Beyond individual differences, situational factors should also
shape susceptibility. The closer people already are to taking some action, the more likely it is
that a dose of word-of-mouth will push them over the edge. People who are searching online
reviews, for example, are often close to being ready to make a purchase, and thus may be
particularly susceptible to influence.
Another potentially interesting question is how multiple instances, or doses, of word-ofmouth aggregate over time. Research distinguishes between simple and complex contagions
(Centola and Macy 2007; Centola 2010). In some cases, awareness may be all that is needed, and
thus one dose of word-of-mouth may be enough to get people to adopt a product or idea (i.e.,
simple contagion). Being forwarded a link to a newspaper article once may get people to take a
look. But for most products, ideas, or innovations, multiple sources of influence increase the
likelihood of adoption (i.e., complex contagion). Trying a new surgical procedure, or even
Word-of-Mouth 14
deciding to see a new movie, may require multiple sources of word-of-mouth before adoption
occurs. In these situations, the persuasive impact of word-of-mouth may be more important.
Research has recognized that some products and behaviors require more doses of
influence, and documented that multiple doses increase adoption, but little empirical work has
examined this area. What types of products tend to be complex contagions (e.g., potentially
newer or riskier ones, Woodside and Delozier 1976)? How does the temporal distance between
doses affect their overall impact (i.e., are two doses this week the same as one this week and one
the next)? Are the behavioral processes behind these effects driven by memory, belief updating,
or some other factor?
Research might also consider how doses of word-of-mouth combine with advertising to
impact behavior. One possibility is that advertising helps spread general awareness and word-ofmouth then persuades people to take action.
A related question is the effect of advertising on word-of-mouth. Advertising not only
combines with word-of-mouth to impact sales, but may boost word-of-mouth as well (Moon,
Bergey and Iacobucci 2010; Onishi and Manchanda 2011; Stacey, Pauwels, Lackman 2012;
Stephen and Galak 2012).10 What types of ads generate more word-of-mouth (Moldovan and
Lehmann 2010) or are more likely to be shared?
This is a particularly interesting question because some of the factors that make ads more
likely to be shared may also make them less persuasive. One might imagine that consumers are
hesitant to share advertisements that seem like direct influence attempts. At the same time, if
advertisements make no attempt to be persuasive, they are less likely to benefit the brand. So it
10
Note that word-of-mouth may also effect advertising. More word-of-mouth, for example, may allow companies
to advertise less because everyone already knows about the product. Word-of-mouth might also impact the content
of advertising. Companies and organizations sometimes design their ads based on the everyday language people are
using to describe the product. Further, if consumers are already talking about certain features of a product,
advertisers may want to highlight other features, or try to stamp out false word-of-mouth by sharing the truth.
Word-of-Mouth 15
may be hard for ads to both be shared and boost brand evaluation or choice. Indeed, research
suggests that virality and ad persuasiveness are negatively correlated; every million more view
an ad receives is associated with 10% lower persuasiveness (Tucker 2011).
One way to address this conundrum may be to generate entertaining content in which the
product or brand is integral to the narrative (i.e., BlendTec’s Will it Blend campaign). Such ads
are interesting enough to be shared, but provide enough information about the brand to boost
brand evaluation, purchase likelihood, and choice after delay (Akpinar and Berger 2012).
Finally, future work might more deeply examine the relative impact of word-of-mouth
and advertising on behavior. Some research suggests that word-of-mouth referrals have a larger
short and longer term effects than media (Trusov, Bucklin, and Pauwels 2009) and that while the
per-event (e.g., one TV or blog post mention) sales impact of earned media is larger than social
media, social media has a larger impact overall because the events are more frequent (Stephen
and Galak 2012). This work highlights that audience size (i.e., number of people reached) and
per-person impact may be two key factors. Television ads, for example, tend to reach more
people than most word-of-mouth conversations (though online ads may have similar reach).
Advertising can also be used to reach many people faster than word-of-mouth usually can.
Compared to a dose of advertising, one might imagine that a dose of word-of-mouth is
more likely to change behavior because it is more persuasive. People likely trust word-of-mouth
more than they trust traditional marketing efforts for a number of reasons. First, consumers
recognize that advertisements are trying to persuade them, and may react against this influence
attempt (Friestad and Wright 1994). Relatedly, word-of-mouth is usually more objective (though
see Tuk, Verlegh, Smidts, and Wigboldus 2009). Ads always say the product is good, so they
are not very diagnostic. People’s friends, however, tend to tell them the truth, so word-of-mouth
Word-of-Mouth 16
is more trustworthy and more persuasive. Consequently, advertising may be most useful for
spreading awareness while word-of-mouth may be most useful for persuasion. Word-of-mouth is
also usually more targeted than advertising. Ads try to appeal only to the target demographic,
but word-of-mouth is even more focused. Consumers tend to seek out the people in their social
network who would be most interested in a given piece of information, and that may be part of
the reason referred customers are more profitable overall (Schmitt, Skiera, and Van den Bulte
2011).
MESSAGE: WHY PEOPLE TALK AND WHAT THEY TALK ABOUT
A great deal of research has examined the consequences of word-of-mouth, but there has
been less attention to its causes, or why people talk about and share certain things rather than
others. Why do certain products get more word-of-mouth? Why does certain online content go
viral? Why do certain rumors spread faster than others?
Early research looked mostly at what topics received more discussion. In 1922, for
example, Henry Moore walked up and down the streets of New York, eavesdropping on what
others discussed. He found that men talked a lot about money and business while women (at
least in the 1920s), talked a lot about clothes. Landis and Burt (1924) found that the prevalence
of different topics varied with the situation: food is often talked about in restaurants while
clothes are talked about near store windows. More recent research found that people often talk
about personal relationships and experiences (Dunbar, Marriott, and Duncan 1997).
Knowing what topics people talk about is interesting, but it says little about the drivers of
discussion, or why people talk about some things more than others. Fortunately, however,
Word-of-Mouth 17
pockets of research in psychology, sociology, communications, and consumer behavior have
begun to consider this issue.
Existing work on the psychological drivers of word-of-mouth can be grouped into four
key areas: Self-Enhancement, emotion, useful information, and accessibility. I review each of
these areas in turn, noting both the underlying psychology or motivation that drives sharing (i.e.,
why people share), as well the types of things it leads people to pass on (i.e., what people are
more likely to talk about and share).
Self-Enhancement
A variety of theories suggest that one reason people share word-of-mouth is to selfenhance, or look good to themselves and others (Dichter 1966; Engel, Blackwell, and Miniard
1993; Gatignon and Robertson 1986; Hennig-Thurau, et. al. 2004; Sundaram, Mitra, and
Webster 1998).
People love talking about themselves. Studies of human conversation suggest that 3040% of everyday speech involves telling others about one’s personal experiences or relationships
(Dunbar, et al. 1997; Landis and Burtt 1924). This percentage is even higher in social media.
Over 70% of Twitter posts are about the self or one’s own immediate experiences (Naaman,
Boase, and Lai 2010).
Neuroscientific evidence suggests that such self-disclosure is intrinsically rewarding
(Tamir and Mitchell 2012). Sharing one’s thoughts and feelings activates the same brain regions
that respond to things like food, money, and seeing attractive members of the opposite sex.
Importantly, this work finds two independent effects. While sharing information with others is
rewarding on its own, there is also independent value for self-referential thought.
Word-of-Mouth 18
But people do not share all their thoughts and opinions equally. The tendency to selfenhance is one of the most dominant human motivations (Fiske 2001). And just like the car
people drive, or the clothes they wear, what people say communicates things about them. If
someone always talks about new restaurants, people may infer that they are a foodie. If someone
always quotes Shakespeare and Thoreau, people may assume they are well-read. Word-ofmouth is a form of self-presentation. Consequently, people should be more likely to share things
that make them look good rather than things that make them look bad. Things that allow them to
gain attention, show connoisseurship, or indicate or achieve status.
Self-enhancement should lead people to talk about interesting, novel, surprising, funny,
or entertaining things. Indeed, ads that are more outrageous, provocative, or funny receive more
views (Tucker 2012) and more interesting or surprising New York Times articles are more likely
to make the paper’s Most Emailed List (Berger and Milkman 2012). Consumers report being
more likely to share word-of-mouth about more original products (Moldovan, Goldenberg, and
Chattopadhyay 2011) and more interesting and surprising urban legends (Heath, Bell, and
Sternberg 2001). Controversy affects word-of-mouth in part because it makes discussion more
interesting (Chen and Berger 2012) and interesting products get more online word-of-mouth
(Berger and Iyengar 2012). Interesting products also receive more face-to-face word-of-mouth
right after people first experience the product (Berger and Schwartz 2011). Interesting, surprising,
novel, outrageous, provocative or funny things should all be entertaining and reflect positively
on the person sharing them, making the sharer seem more interesting, cool, and in-the-know.
Self-enhancement also affects whether people share positive or negative word-of-mouth.
Most people would prefer not to be seen as a Debbie Downer, so sharing things that make others
feel positive rather than negative should facilitate that goal. Consistent with this notion, more
Word-of-Mouth 19
positive New York Times articles are more likely to be highly shared (Berger and Milkman 2012).
Self-enhancement motives also impact whether people share positive or negative experiences.
Some data suggests that there are more positive than negative reviews (Chevalier and Mayzlin
2006; East, Hammond, and Wright 2007; Fowler and De Avila 2009). One reason may be that
talking about positive experiences serves as evidence of one’s expertise (i.e., I make good
choices, Wojnicki and Godes 2011).
Other work, however, suggests that negative word-of-mouth may be self-enhancing.
Book review writers were seen as more intelligent, competent, and expert when they wrote
negative as opposed to positive reviews (Amabile 1983). Similarly, concerns about public
evaluation led people to express more negative ratings in some situations (Schlosser 2005).
So when is positive versus negative word-of-mouth more self-enhancing?
One moderating factor may be whether the item or experience being discussed signals
something about the speaker. When someone chooses a restaurant, or a piece of online content
to forward, the positivity or negativity of that experience or item reflects back on them. If it is
good (bad) that makes them look good (bad). Consequently, people may spread more positive
word-of-mouth to show they make good choices. If the reviewer or rater did not choose the item
or experience they are rating, however, then whether that thing is good or bad signals less about
them. Consequently, people may spread negative word-of-mouth to show they have
discriminating taste.
Consistent with this perspective, research finds that who people are talking about
moderates the valence of word-of-mouth they tend to share (De Angelis, Bonezzi, Peluso,
Rucker, and Costabile 2012). People generate positive word-of-mouth when talking about their
own experiences but transmit negative word-of-mouth when talking about others’ experiences, in
Word-of-Mouth 20
part because it makes them look relatively better than others. When transmitting word-of-mouth
about someone with whom they are closely attached, however, people share positive word-ofmouth because talking about close others reflects on them as well (De Angelis et al 2012).
Self-enhancement also impacts what people talk in about in a host of other ways. The act
of lying, for example, is partially driven by impression management concerns (DePaulo, Kashy,
Kirkendol, & Wyer, 1996). People lie to protect their sense of self-worth and self-image
(Sengupta, Dahl, and Gorn 2002), particularly in the face of negative social comparison
information (Argo, White, and Dahl 2006). Self-enhancement may also lead people to talk about
things that connote status or expertise (e.g., luxury, high priced, exclusive, or scarce items).
Emotion
Experiencing emotion also boosts interpersonal communication. A good deal of research
in psychology has investigated the social sharing of emotion (see Rime 2009 for a review). This
work looks at emotional events, such as seeing a car crash or getting promoted, and examines
when, why, and how people share these emotion inducing experiences with others. Some
research, (e.g., Mesquita 1993 and Vergara 1993), for example, suggests that people share 90%
of their emotional experiences with others (Rime et al., 1992; also see Walker et al. 2009).
Experimental work shows that emotion boosts sharing across a variety of domains.
Movies are more likely to be discussed, and news articles as more likely to be highly shared, if
they are higher, rather than lower, in emotional intensity (Berger and Milkman 2012; Luminet, et
al. 2000). People are more willing to forward emails with higher hedonic value (Chiu et al. 2007)
and share urban legends that evoked more disgust, interest, surprise, joy, or contempt (Heath, et
al. 2001). Highly satisfied and highly dissatisfied customers are more likely to share word-of-
Word-of-Mouth 21
mouth (Anderson 1998). Looking across a range of emotions, people were more willing to share
more emotional social anecdotes (Peters, Kashima, and Clark 2009).
There are a number of reasons why people might share emotional content or experiences.
First, sharing can provide catharsis and help people deal with their emotional states (Pennebaker
1999; Pennebaker, Zech, and Rimé 2001). Second, emotional stimuli often elicit ambiguous
sensations (e.g., am I angry, sad, or both?), and through talking about and sharing with others,
people can gain a deeper understanding of how they feel (Rime, Mesquita, Philippot, and Boca
1991). Third, to the extent that emotional material challenges people’s beliefs or way of seeing
the world, they may share it with others to cope or reduce feelings of dissonance (Festinger,
Riecken, and Schachter 1956). Fourth, sharing an emotional story or narrative with others
increases the chance that they will feel similarly, which in turn, facilitates empathy and can
deepen social connection (Peters and Kashima 2007). Some have even argued that this bonding
function is the main reason language evolved in the first place (Dunbar 2004).
While these benefits are valuable consequences of emotion sharing, it is unclear whether
they actually cause people to share emotional content. Researchers have theorized that people
share word-of-mouth to reduce anxiety (Sundaram, et al 1998), for example, or vent negative
feelings (Hennig-Thurau, et. al. 2004), but it is unclear whether these consequences truly drove
people to share in the first place, or are merely by-products of such sharing.
Beyond emotion in general, it is also important to consider whether different emotions
have different effects on transmission. This question is not only important from a practical
standpoint, but also sheds light on the underlying mechanisms behind emotions influence on
social transmission.
Word-of-Mouth 22
Valence. The main way emotions differ is their valence, or positivity and negativity.
Certain emotions (e.g., excitement) are positive, while others (e.g., anxiety) are negative. One
intuitive question is whether positive and negative emotions have a differential impact on
transmission. Are people equally likely to talk about a positive or negative emotional experience?
Share positive and negative word-of-mouth?
Note that this question is different than simply asking whether there is more positive or
negative word-of-mouth overall. Research suggests that there is more positive than negative
word-of-mouth (Chevalier and Mayzlin 2006; East, Hammond, and Wright 2007), but this could
simply reflect base rates of positive and negative events (i.e., more things are good than bad),
rather than preferential transmission based on valence (i.e., given both experiences, people prefer
to share positive word-of-mouth). Thus it is important to separate preferential transmission from
mere base rates (see Berger and Milkman 2012; Godes et al. 2005).
There are reasons to believe that either positive or negative things could be more likely to
be shared. Bad news (e.g., earthquakes and product recalls) often spreads quickly, and the old
news adage that “if it bleeds, it leads,” is based on the idea that negative content (e.g., tragedy or
crime) is most likely to get attention and interest. Negative information has survival value
because it tells people what to avoid, and across a range of domains bad things have a stronger
impact than good ones (see Baumeister et al. 2001 for a review). At the same time, positive
content provides information about potential rewards (i.e., this restaurant is worth trying) and
sharing positive or upbeat content can boost the receiver’s mood. Further, as noted in the section
on self enhancement, people may prefer to share positive things because they want to be
associated with making others feel better rather than bringing them down. Being a Positive Polly
rather than a Debbie Downer.
Word-of-Mouth 23
There is much more work to be done to examine when and why positive and negative
things are shared, but a few papers have examined this area empirically. People report greater
willingness to share pleasant ads than unpleasant ones (Eckler and Bolls 2011) and more positive
news articles are more likely to be highly shared (Berger and Milkman 2012). Similarly, highly
controversial topics induce discomfort which decreases people’s willingness to talk about them
(Chen and Berger 2012).
But the issue is likely more complicated than just positive gets shared and negative does
not. While positive news articles are more likely to be highly shared, negative articles are more
likely to make the list than articles that evoke no emotion at all (Berger and Milkman 2012).
Congruence may play an important role, where people prefer to pass along news that is
congruent with the valence of the domain in question (Heath 1996; also see Donovan, Mowan
and Chakaborty 1999). So in negative domains, like crime, people are more likely to pass on
more negative stories, while in positive domains, like vacations, people are more likely to share
more positive stories. As discussed in the Self-Enhancement section, people may also be more
willing to share positive things when talking about themselves and negative things when talking
about others (De Angelis et al 2012). In addition, people with high needs for uniqueness may
avoid sharing positive word-of-mouth (Cheema and Kaikati 2010), or talk positively but
discourage adoption (Moldovan, Steinhart, and Ofen 2012), to prevent others from imitating
them.
Arousal. Emotions also differ in their level of physiological arousal. Physiological
arousal is an excitatory state characterized by increased heart rate, blood flow, and a readiness
for action (Heilman 1997). Some emotions, like anxiety or excitement are high arousal, while
others, like sadness or contentment, are low arousal (Barrett and Russell 1998). Anxiety and
Word-of-Mouth 24
sadness are both negative emotional states, for example, but they differ in the level of arousal
they induce. Anxiety is associated with activation while sadness is associated with deactivation.
Research suggests that high arousal emotion increases social transmission. News articles
that evoke more high arousal emotions, like awe, anger, or anxiety, are more likely to be highly
shared, while articles that evoke more low arousal emotion, like sadness, are less likely to be
highly shared (Berger and Milkman 2012). Taking one piece of content, and manipulating how
much anger, amusement, or sadness it evokes has similar effects. People are more willing to
share an article when it evokes more anger or amusement and less willing to share an article
when it evokes more sadness. These effects are mediated by participants’ felt arousal. Arousal
has such a strong impact on sharing that even incidental arousal, from watching a scary or funny
film clip, or running in place, can spillover and boost sharing of unrelated content (Berger 2012).
The idea that arousal increases sharing helps explain a diverse set of prior findings. Early
work on rumor transmission suggested that rumors flourished in times of conflict, crisis, and
catastrophe, due to the generalized anxiety those situations induce (Koenig 1985, see Heath et al
2001). More recent work suggests that extremely dissatisfied customers share more word-ofmouth (Richins 1983) and that ads that evoke more amusement are viewed more (Tucker 2012).
Arousal may help integrate these disparate findings. Anxiety, extreme dissatisfaction, and
amusement are all high arousal states that should increase social transmission. Arousal may also
help explain the increased sharing of surprising, novel, or outrageousness content (Berger and
Milkman 2012; Heath, et al. 2001; Moldovan, et al 2011; Tucker 2012). People may share such
content to self-enhance, but they may also share it because of the arousal watching it evokes.
The underlying mechanism(s) behind the effect of arousal on transmission, however,
remains unclear. One possibility is that arousal generally increases action, and sharing happens
Word-of-Mouth 25
to be an action. Another possibility is misattribution, whereby arousal causes people to think
content is better or more interesting, and thus more worthy of being shared. A third possibility is
that arousal increases self-focus (Wegner and Giuliano 1980), which might lead people to weigh
their own opinions more when deciding what to share. The effects of arousal on transmission are
likely multiply determined, but the different mechanisms have different implications for when
the effects should be larger.
Other Emotional Moderators. Other factors also likely moderate the impact of emotion
on sharing (see Rime 2009). Shame and guilt, for example, are two emotions that seem to lead
to less sharing, rather than more (Finkenauer and Rime 1998), potentially because sharing such
things should make people look bad. Extremely strong emotions (e.g., very high levels of fear)
may also stunt sharing as they generate a state of shock that decreases the chance people take any
actions.
Useful Information
Another factor that shapes interpersonal communication is useful information.
Psychologists, sociologists, and folklorists have long theorized that people share rumors,
folktales, and urban legends not only for entertainment, but also because they contain practically
valuable information or social morals (Allport and Postman 1947; Rosnow 1980; Shibutani,
1966; Rosnow and Fine, 1976; Brunvand 1981). People share rumors to help “understand and
simplify complicated events,” (Allport and Postman 1947, p. 5) and tell legends “not only
because of their inherent plot interest but because they seem to convey true, worthwhile and
relevant information…” (Brunvand, 1981, p. 11). Indeed, there is some evidence that stories that
are more useful (i.e., people would change their behavior upon hearing them) are more likely to
be shared (Heath, et al. 2001).
Word-of-Mouth 26
Some theories of gossip (e.g., Baumeister, Zhang, and Vohs 2004) have taken a similar
approach, arguing that gossip is a key source of cultural learning. Gossip often implicitly
communicates societal rules through stories, showing the negative repercussions that befell
someone who violated social norms. Rather than trying to acquire information through trial and
error, or direct observation of others (which may be difficult), gossip serves as a form of
observational learning, allowing people to acquire relevant information quickly and easily.
Others have argued that one of the main functions of conversations is social grooming or to
acquire relevant information about other people (Dunbar, et al. 1997; Dunbar 1998).
Some consumer behavior findings are consistent with these theoretical perspectives.
Experimental work finds that people are more willing to share marketing messages that have
more utilitarian value (Chiu et al. 2007) and suggests that usefulness may be particularly relevant
in shaping the valence of word-of-mouth (Moldovan, et al. 2011). Empirical analyses find that
more useful news articles are more likely to be highly shared (Berger and Milkman 2012).
But while it is clear that people share useful information, the exact motive for sharing this
type of content may be multiply determined. One reason people share useful information may be
altruism, or the desire to help others (Dichter, 1966; Engel et al. 1993; Hennig-Thurau et al. 2004;
Price et al. 1995). Critical interviews, for example, suggest that over 20% of word-of-mouth
conversations were motivated by the desire to help others avoid problems or make satisfying
purchase decisions (Sundaram, et al. 1998). Other drivers are more self-focused. Useful
information has social exchange value (Homans 1958) which can generate future reciprocity
(Fehr, Kirchsteiger, and Riedl 1998). People may also share useful content because it is selfenhancing, and reflects positively on them (i.e., makes them seem like they know useful things).
Which of these motives is most important, and when, remains unclear.
Word-of-Mouth 27
People also seek useful information, or advice, from others (Dichter 1966; HennigThurau et al. 2004; Sundaram et al. 1998). Theoretical frameworks suggest that such information
may help reduce risk, decrease search time, and allow people to support and justify their
decisions (Engel, Blackwell, and Miniard 1993; Gatignon and Robertson, 1986; Hennig-Thurau
and Walsh 2003). That said, relatively little empirical work has actually looked at when and why
people seek advice, so this may be a fruitful area for future research
Accessibility
Accessibility also impacts what people talk about and share. Products, information, and
conversation topics more broadly vary in their accessibility (Higgins and King 1981; Wyer and
Srull 1981). Some things are more top of mind, while others are less so. But stimuli in the
environment, such as sights, sounds, or smells, can act as cues, or triggers, activating associated
concepts in memory and making them more accessible (Higgins, Rholes, and Jones 1977). This
activation can then spread to related concepts through an associative network (Anderson 1983;
Collins and Loftus 1975). So eating peanut butter not only makes peanut butter more top-ofmind, but it also makes its frequent partner jelly more accessible. A great deal of research has
shown how accessibility affects judgment and choice (Feldman and Lynch 1988; Hauser 1978;
Nedungadi 1990; see Lynch and Srull 1982 for a review).
Accessibility also shapes word-of-mouth. Consistent with the notion that people tend to
talk about situation consistent topics (Landis and Burt 1924), people reported that 80% of wordof-mouth about a new coffee product was driven by related conversational or environmental cues
(e.g., seeing an ad, but also simply drinking coffee or talking about food, Belk 1971). Similarly,
many word-of-mouth referrals seem to be driven by related topics happening to be discussed
Word-of-Mouth 28
(Brown and Reingen 1987). Cues can also be internal. People who care a lot about a particular
brand, or are heavily involved in a certain product category should have those constructs more
chronically accessible, which should lead them to be more likely to be discussed.
More recent empirical work supports this suggestion, finding that products that are cued
or triggered more frequently by the surrounding environment get 15% more word-of-mouth
(Berger and Schwartz 2011). Experimental evidence underscores this notion, and shows that
increasing the prevalence of triggers for a product increases the amount of word-of-mouth it
receives. Similarly, research shows that compared to consumers’ opinions, certainty information
(i.e., consumers’ feeling of certainty or uncertainty associated with an opinion) is less likely to be
shared because it is less accessible (Dubois, Rucker and Tormala 2011).
The effect of public visibility on word-of-mouth may also be driven by accessibility.
Some products and behaviors (e.g., shirts and greetings) are more public while others (e.g., socks
and donations to charity) tend to be more private. This increased visibility, in turn, should
increase the chance that others see and talk about those products. People talk about shirts more
than socks, for example, because the former is more likely to be seen, made accessible, and
discussed. Indeed, publicly visible products receive 8% more word-of-mouth (Berger and
Schwartz 2011).
Accessibility may also explain why people tend to talk about things they have in common
with others (Clark 1996; Stalnaker 1978). Consider how often people talk about the weather,
how teaching is going (if they’re faculty members), or how classes are going (if they’re students).
These subjects are not the most interesting, but they are common ground (Grice 1989), or topics
that are shared across people. As discussed later in the section on audience tuning, conversation
partners should automatically activate related conversation topics and make them more
Word-of-Mouth 29
accessible. Consequently, topics that are common ground should automatically be more top-ofmind. Even controlling for actual performance, for example, more familiar baseball players get
more mentions in online discussion groups (Fast, Heath, and Wu 2009). More familiar topics
should be more top-of-mind and thus more likely to be discussed.
That said, discussing common ground topics may also be driven by self-enhancement and
the desire for social connection. Having things in common facilitates social bonding, and
particularly when meeting new people, bringing up topics that everyone can relate to increases
the chance that conversation goes well, making the sharer look better as a result.
Other Drivers of Word-of-Mouth
Though self-enhancement, emotion, useful information, and accessibility are the four
drivers of word-of-mouth that have received the most empirical support, other potential drivers
that have also been suggested. Some have theorized that people share word-of-mouth to enact
vengeance, or punish a company for a bad product or negative service experience (Richins 1983;
Sundaram et al. 1998). This could be placed under emotion, as it seems driven in part by
emotional arousal, but it also seems slightly distinct. Others have suggested that people share to
bond with others (Dunbar 2004; Hennig-Thurau, et. al. 2004). The fact that neurotic individuals
microblog more frequently (e.g., post more Facebook status updates, Buechel and Berger 2012)
is consistent with this notion, as is the finding that sharing emotions deepens social connections
(Peters and Kashima 2007).
Word-of-Mouth 30
Open Questions
In addition to thinking about how certain factors affect why people talk and what they
talk about, research might also examine when different word-of-mouth drivers matter more. Self
enhancement, emotion, useful information, and accessibility all influence word-of-mouth, but
when does each play a relatively larger or smaller role?
One important moderator may be memory. Sometimes people talk about a shirt they just
bought or a thing that happened to them last night. Other times they talk about a shirt they
bought last month or something that happened to them last year. These examples distinguish
between immediate and ongoing word-of-mouth. Immediate word-of-mouth describes mentions
that happen right after people first experience a product. Ongoing word-of-mouth describes the
product mentions that occur in the weeks and months that follow.
Certain product characteristics may be associated with more word-of-mouth over one of
these time horizons than the other. Some research suggests that more interesting products only
get more immediate word-of-mouth, while products that are cued more frequently, or are more
publicly visible, receive both more immediate and more ongoing discussion (Berger and
Schwartz 2011). People may talk about interesting things right after they happen, but for
something to continue to be talked about, people may need to be cued or triggered to think about
it. Thus self-enhancement and emotion may shape whether people talk about things right after
they happen, but as time elapses memory (i.e., accessibility) plays a larger role.
Memory based processes like accessibility may also play a larger role in communication
channels where people are more likely to talk about things that happened further in the past.
Online content often seems to be shared soon after it is experienced. People watch a video, or
read an article, and then share it or not. Face-to-face discussion, however, often seems to involve
Word-of-Mouth 31
things that happened more distally. Thus memory based processes (like accessibility) may play a
larger role in face-to-face than online word-of-mouth.
The audience may also moderate which word-of-mouth drivers are more important. We
discuss audience effects in more detail below, but intuition suggests people should be more
likely to care about self-enhancement when sharing with acquaintances (vs. friends) or when
discussion is public (e.g., on Facebook) rather than private.
Research might also more deeply examine how people say what they say. Emotional
arousal might lead people to talk about an experience, for example, but there are a variety of
ways people could talk about that same event. They could use different words, be more or less
assertive, and express varying degrees of certainty. Some research has begun to look at language
use, investigating explaining language (Moore 2012), expressions of modesty (Packard, Gershoff,
and Wooten 2012), and linguistic mimicry of conversation partners (Moore and McFerran 2012),
but much more remains to be done.
AUDIENCE
Another major question is who people share word-of-mouth with. People have a variety
of social ties: friends, neighbors, family members, acquaintances, and colleagues. Even within a
particular category, each tie has different interests, expertise, likes and dislikes. When do people
share word-of-mouth with certain people rather than others? And what role does the audience
play in what gets shared?
Word-of-Mouth 32
Strong vs. Weak Ties
One audience factor that shapes what people talk about and share is the strength of the
social tie. As noted earlier, research distinguishes between strong and weak ties; people we
know well, trust, and/or speak to often, versus acquaintances with whom we do not have as
strong a connection (Granovetter 1973; Brown and Reingen 1987).
Tie strength should affect what people share in a number of ways. One relates to the
value of information. When the moral hazard, or value of information is high, people may only
share with strong ties (Frenzen and Nakamoto 1993). If there is a restricted sale that only a
certain number of people can get access to, for example, people may only share that information
with close friends. But when the information value is lower, or the consequences less restrictive,
people seem to be more willing to share that information with their weak ties as well.
Tie strength should also impact whether people are willing to share things that are
revealing, potentially damaging to the self, or controversial. People tend to share unusual or
emotional experiences with close others or individuals they know well (Brown and Reingen
1987; Heath, et al. 2001; Rime 2009). Because we feel a closer bond with our strong ties, we
may be more willing to reach out to them, particularly when we want to talk about things that are
embarrassing, damaging, or negative (e.g., a love of pop music or dealing with a tough breakup).11 Similarly, people are more willing to talk about controversial topics with friends (than
strangers) because it reduces the discomfort from talking about dicey, potentially divisive issues
(Chen and Berger 2012). That said, one could argue that people may feel more comfortable
saying embarrassing things to strangers because we don’t see them often. Further, people are
11
Though people certainly share embarrassing things over social media, which is sent primarily to their weak ties,
this seems more like an effect of social presence rather than tie strength per se. Because the audience isn’t actually
present, people may feel more uninhibited.
Word-of-Mouth 33
more likely to lie to friends rather than strangers because they are relevant social comparison
targets (Argo, et al. 2006).
Some work has also examined how tie strength and referral rewards interact (Ryu and
Feick 2007). This work suggests that while consumers receive an economic benefit from referral
rewards, the potential cost is a dissatisfied receiver and the self-perception that one’s personal
recommendation can be bought. They find that people are more likely to naturally tell their
strong ties about a product they liked, but providing a reward for referral increases the likelihood
of telling weaker ties.
Finally, tie strength also affects what people share through activating constructs related to
psychological distance. Strong ties should be represented as closer to the self than weak ties.
This difference in psychological distance should change construal level (Trope and Liberman
2010), whereby close others activate a concrete mindset while distant others activate an abstract
mindset. Once activated, these mindsets may change what people think about and share. Product
disadvantages (cons) are often more concrete than advantages (pros, Eyal et al. 2004), for
example, and as a result, sharing with close others prompts people to talk more about cons than
sharing with distant others (Dubois, Bonezzi and De Angelis, 2012).
Audience Size
Sometimes people talk to a large audience, chatting with a group of co-workers or
emailing a bunch of friends. Other times people talk to a small audience, chatting with just one
co-worker or emailing with just one friend. The former can be described as broadcasting, while
the latter can be described as narrowcasting.
Word-of-Mouth 34
These differences in audience size can impact what people discuss (Barasch and Berger
2012). Broadcasting is often public, and may involve communicating with weaker social ties
that do not know the sharer as well. Consequently, broadcasting should encourage selfenhancement. Narrowcasting, on the other hand, makes people less egocentric because it focuses
them on their audience. Consequently narrowcasting leads people to focus less on selfpresentation and more on what the audience would find useful.
Broadcasting also encourages acknowledging multiple perspectives while at the same
time paradoxically dumbing down content to the lowest denominator. Larger audiences often
contain many different viewpoints. Thus sharers must appeal to different people with the same
message, presenting multiple viewpoints at the same time (Schlosser 2005), and adjusting the
message to offer a more balanced opinion (Fleming et al. 1990). Finding something everyone
can relate to may also become more difficult as audience size increases, which could lead
simpler, more basic, or less controversial things to be discussed.
Audience Tuning
People also engage in audience tuning, tailoring what they share to the knowledge,
attitudes, and interests of their audience (Clark and Marshall 1981; Clark and Murphy 1982;
Higgins 1981; Higgins 1992; Krauss and Fussell 1991).12 When people are talking to foodies,
they mention restaurants, but when they are talking to sports junkies, they mention football. Just
like other stimuli in the environment, conversation partners can act as triggers, activating related
concepts in memory (Fitzsimons and Bargh 2003) and leading them to be more likely to be
discussed. The presence of someone who likes football also makes football a more relevant
conversation topic (Grice 1989; Sperber and Wilson 1986; also see Berger and Heath 2005).
12
This, may in turn, affect what the communicator remembers (Higgins 1999)
Word-of-Mouth 35
The reverse should also occur, whereby content activates related individuals. Reading a
newspaper article about football should increase the accessibility of social ties who might find
that article interesting or useful.
The increased accessibility of content-related receivers has interesting implications for
whether broadly or narrowly relevant content is more likely to be shared. Some information (e.g.,
an article about football or American food) has a broader potential audience than other
information (e.g., an article about water polo or Ethiopian food). Consequently, intuition
suggests that broadly-relevant content should be more likely to be shared.
Narrowly relevant content, however, may benefit from stronger associations with
particular individuals. While narrowly relevant content is, by definition, not as broadly
interesting, it is more likely to be tied one or two particular individuals in one’s social network.
Further, because it is tied to fewer individuals, those ties are likely to be stronger (i.e., the fan
effect, Anderson 1974; 1983). Most people don’t eat Ethiopian food, but because of that, it is
more likely that a particular social tie (or two) is strongly activated when someone comes across
an article about Ethiopian food. This stronger activation, in turn, may increase the likelihood
that the article is shared, because people may use activation strength as a signal that content is
worth sharing. Thus while broadly relevant content could be shared with more people, narrowly
relevant content may be more likely to be shared because it strongly activates a few people who
might find the content highly relevant.
This discussion highlights the important distinction between sharing likelihood and
number of shares overall. In this case, there is likely more overlap across people in what is
broadly-relevant than what is narrowly relevant. Most people have some friends that like
American food, but while some people may have a few friends that like Ethiopian food, and
Word-of-Mouth 36
other people have a few friends who like water polo, most people may not have any friends that
like either. Consequently, compared to broad relevant topics, each person may be more likely to
share whatever topic is narrowly relevant to them, but broadly relevant topics may get more
overall shares because they could be shared by, and to, many more people. The underlying
psychological driver of sharing is the same, but what it leads people to share may differ across
different individuals.
Open Questions
Beyond tie strength, audience size, and tuning, however, there has been little work
examining the relationship between audience and sharing. There may be a variety of other
audience differences that shape what people share.
COMMUNICATION CHANNELS
Consumers communicate through different channels. They talk face-to-face, on the phone,
and in chat rooms; through blogs, on Facebook, and over text. Almost all word-of-mouth
research, however, only examines data from a single channel, limiting the ability to speak to the
role of channels in word-of-mouth. Might the channel consumers communicate through affect
what they talk about, and if so, how?
Computer-Mediated Communication
One difference between communication channels is whether they are computer-mediated.
Though some work has used face-to-face word-of-mouth (e.g., Berger and Schwartz 2011;
Brown and Reingen 1987; Frenzen and Nakamoto 1993; Godes and Mayzlin 2009; Granovetter
Word-of-Mouth 37
1973; Iyengar, et al. 2010; Richins 1983) most recent word-of-mouth research using field data
has focused on computer-mediated commination like online reviews (Chevalier and Mayzlin
2006; Moe and Trusov 2011), social media mentions (Stephen and Galak 2012), newsgroups
(Godes and Mayzlin 2004), and blogs (Dhar and Chang 2009).
Various perspectives have theorized about how computer-mediated communication
shapes interpersonal relations (see Walther 2011 for a review). When people communicate faceto-face, they often use tone of voice and other nonverbal cues (e.g., appearance, facial
expressions, and posture) to make inferences about others. These features are absent from
computer-mediated communication (unless people video chat), which can make it difficult to
communicate accurately and effectively (Epley and Kruger 2005; Kruger, Epley, Parker, and Ng
2005). This had led some to argue that computer-mediated communication is more impersonal
and makes it difficult to manage impressions (e.g., Culnan and Markus 1987).
More recently, however, the hyperpersonal model (Walther 1996; 2007; 2011) has argued
that computer-mediated communication actually facilitates self-presentation and selfenhancement. Since people are physically separated, they do not have to monitor the nonverbal
signals they or their conversation partner(s) sends, allowing them to avoid sending mistaken
signals and freeing up cognitive resources to focus on what they want to say. Further, while
face-to face interaction tends to be synchronous (i.e., almost no delay between conversational
turns), computer-mediated communication is usually asynchronous (i.e., people respond to
emails or texts hours, rather than seconds later). This asynchronicity may allow people to
construct and refine the messages they send. They can abort messages and begin anew, or go
back and change what they wrote before they send it. Asynchronicity may then allow them to
Word-of-Mouth 38
strategically develop and edit how they present themselves, selecting and transmitting desired
information.
Little empirical work has investigated the consequences of these differences, but they
should have important implications for what people talk about and the nature of communication
more generally.
One paper, for example, suggests that channel synchronicity moderates whether interest
drives discussion (Berger and Iyengar 2012). While one might think that interesting products are
more likely to be talked about more than boring ones, this may only be the case in more
asynchronous channels where people have time to think about what to say (i.e., online
communication and texting). When people talk face-to face or over the phone, interesting
products are not talked any more likely to be discussed. Further, merely having people pause
before they talk face-to-face leads more interesting products to be discussed. This suggests that
self-enhancement has a bigger impact on what people talk about when they have time to think
about what to say. Along these lines, other work suggests that requests made by email are seen
as more polite than those made by voicemail, ostensibly because people have time to compose
their requests (Duthler, 2006). In instances where people do not have as much time to think,
however, accessibility likely drives discussion.
The content of computer-mediated communication may also be more interesting because
communication is relatively optional. Rather than sitting next to someone and feeling the need to
fill conversational space, most social media posts do not require responses. Further, social
norms of politeness make it harder to exit a boring face-to-face conversation than end an email
chain. Consequently, one could imagine that computer-mediated conversations are shorter, more
interesting, and more goal directed (e.g., driven by the desire to find particular information). So
Word-of-Mouth 39
people may still tweet about what they had for lunch, but on average computer-mediated
conversations may be less vacuous.
The “cost” of computed-mediated communications may also be higher. One could argue
that writing is more effortful than speech, and if so, conversations should be shorter and people’s
willingness to talk about unimportant issues may decrease. Factors that make typing relatively
harder (e.g., smaller keyboards on smartphones than laptops) may also moderate these effects.
Computer-mediated interactions may also impact communication through their
permanency. Compared to speaking, any sort of writing tends to provide a more permanent
record of what was said. This suggests that people might be less likely to say embarrassing
things, and more likely to self-enhance, through computer-mediated communication. That said,
the fact that others are not present during the formation of the communication may lead people to
be less aware of their audience, which could lead more embarrassing things to be shared.
Finally, text-based communication may also have different effects on the information
sharer. Warm interpersonal contact can help release oxytocin and reduce stress, but instant
messaging does not seem to provide the same beneficial responses (Seltzer, Ziegler, and Pollak
2010). Similarly, research suggests that compared to conversations that involve voice, text-based
communication lead observers to infer that the communicator possess weaker mental
capacities—less agency, less experience, less basic human nature, and less uniquely human traits
(Epley and Schroeder 2012).
Identifiability
Another way conversation channels differ is the degree to which communicators are
identifiable. People often post reviews, blog, or tweet anonymously with usernames that readers
Word-of-Mouth 40
may not easily be able to trace back to their actual identity. In face-to-face discussions, and even
on Facebook, however, identities are disclosed, and people know who they are talking to.
Identifiability should lead self-enhancement concerns to play a larger role (Goffman
1959). Similar to effects of public consumption (Ratner and Kahn 2002), identifiability should
make people more conscious of what they are saying and what it communicates about them
(Schlosser 2005). Along these lines, research on controversy and conversation shows that people
are less willing to talk about controversial topics when their identity is disclosed (Chen and
Berger 2012). Similarly, research suggests that public discussion may lead people to adjust their
attitudes downward so as not to appear indiscriminant (Schlosser 2005). Anonymous posting,
however, should reduce identity signaling concerns. This may be one reason people say nasty or
repulsive things in online forums where their identity is not disclosed.
Audience Size
Though it is not an effect of channel per se, channels also tend to differ in the size of the
audience. Some channels (e.g., blog posts and Facebook status updates) tend to involve
broadcasting, while others (e.g., most phone calls or email) involve narrowcasting. These
differences should lead to the same effects as noted in the Audience Size portion of the Audience
section.
Channel Selection
Most of this discussion has centered on how channels impact communication, but people
may also select different channels depending on what they want to discuss. People who are
embarrassed about a particular preference or interest, for example, may use computer-mediated
Word-of-Mouth 41
channels that allow them to solicited information while remaining anonymous. We discuss this
issue of channel selection versus channel influence in more detail below.
BROADER QUESTIONS FOR FUTURE RESEARCH
There are many interesting and important questions related to word-of-mouth that would
benefit from further research. While the preceding sections have raised some of them, a few
broader questions and points are worth considering.
(When) Is Word-of-Mouth Goal Driven?
One overarching question is the degree to which word-of-mouth is goal-driven. Most
research has assumed that word-of-mouth is motivated action. Researchers ask questions like
“what motivates people to talk about their experiences?” (Dichter 1966, p. 147) or set out to
“reveal the underlying motives for consumers engaging in both positive and negative word-ofmouth,” (Sundaram, et al. 1998, p. 527). Most work on self-enhancement takes a similar
perspective, suggesting that people choose to talk about things that make them look good.
In using words like motivates and choose, however, research has implicitly assumed that
word-of-mouth is driven by some sort of goal. To look good. To help others. As we’ve
discussed, these goals or motivations certainly shape some word-of-mouth. When going on a
date, or interviewing for a job, people care a lot about how they are perceived, and may be
motivated to talk about things that help others or make them look good.
Word-of-Mouth 42
But most interpersonal communication does not seem so motivated. What people talk
about when they have lunch with their friends or grab a beer after work seems less like goaldriven choices and more like small talk about whatever happens to be going on that day.
The importance of arousal and accessibility in driving word-of-mouth is consistent with
this perspective. The fact that people are more likely to share things that make them angry or
anxious (Berger and Milkman 2012) or after they have exercised (Berger 2011) seems to have
little to do with a motivation to appear a particular way. Similarly, the fact that people are more
likely to talk about accessible things has little to do with decisions or goals. In fact, while
intuition and practitioners suggest that interesting products should get more word-of-mouth than
boring ones, some data suggests that this only occurs for online conversations (Berger and
Iyengar 2012), or for immediate word-of-mouth in offline conversations (Berger and Schwartz
2011). Thus, like many other behaviors (Bargh and Chartrand 1999), most word-of-mouth may
not be as motivated as once imagined.
Situational factors likely moderate when word-of-mouth is goal-driven versus shaped by
accessibility. Communication over most channels is voluntary. People don’t have to send a text
or respond to a blog post, and so the decision to share word-of-mouth over these channels is
almost always a choice. Some face-to-face communication, in contrast, is imposed by the
situation. It is awkward to have dinner in silence, or not say anything when you run into a
colleague on the subway, so the situation pushes people to talk. In these instances, the goal is
simply to say something rather than say nothing. Further, given the expected synchronicity of
the conversation (i.e., long pauses are uncomfortable), there is little time to select and craft the
best possible thing to say. So rather than talking about the most self-enhancing or useful thing,
people may be more likely to talk about what is top of mind. In such situations, the act of saying
Word-of-Mouth 43
something may be motivated (i.e., the desire to avoid awkward pauses in conversation), but what
in particular people say may not be as motivated. This suggests that face-to-face word-of-mouth
is driven more by accessibility, while word-of-mouth over the phone, text, or online, may be
more goal driven.
When Is Word-of-Mouth More Content versus Context Driven?
Situational factors should also shape whether word-of-mouth is content or context driven.
Some word-of-mouth is driven by the content itself. People find a useful article or have a highly
emotional experience and they just have to pass it on. In these situations, people seem to share if
the content is above some threshold (e.g., of interest, utility, or emotion).
In other situations (e.g., sitting face-to-face at dinner), conversation is exogenously
imposed by the context. So the question becomes less about whether something is worth talking
about, and instead given that conversation is occurring, which of the things that could be
discussed are actually discussed.
In situations where word-of-mouth is context driven, the channel and audience are fixed,
so the only degree of freedom is what to talk about. In situations where word-of-mouth is
content driven, however, the sharer can decide whether to share, what channel to share over, and
who to share with.
Though this distinction is intuitive, it likely has important implications for what gets
discussed. Context driven word-of-mouth should depend a lot on accessibility, where the
audience and other surrounding factors act as triggers to bring up certain things to discuss. In
these instances, the key question may be given that something is top-of-mind, should it be talked
about or held back.
Word-of-Mouth 44
Content driven word-of-mouth, however, raises many more questions. How do people
decide who to share something with? Is the audience simply driven by accessibility, or who
comes to mind, and fit, or how useful or valuable that potential receiver might find the content?
What role does the strength of tie or frequency of interaction play? And how do people decide
what channel to share the content through? Is channel selection simply driven by convenience?
Some work suggests that at least in the online sphere, where people post a review may depend in
part on where they think it will get the most attention (Chen and Kirmani, 2012). Further
research might delve into these issues more directly.
When Is Word-of-Mouth More Source versus Audience Driven?
Another general question is how much the audience matters in word-of-mouth. One
could argue that most word-of-mouth is audience driven. After all, people are not just sharing
word-of-mouth, they are picking a particular person or people to share that word-of-mouth with.
Further, as shown in work on audience tuning (Clark and Murphy 1982; Higgins 1992) people
seem to tailor what they are saying to their audience, sharing things that are at least moderately
relevant or interesting to the people they are communicating with, particularly when those
individuals are made salient.
At the same time, however, the fact that arousal boosts sharing suggests that internal
sharer states play an important role in whether transmission occurs. Similarly, people suggest
that most of the reasons why they share word-of-mouth are self-focused (Stephen and Lehmann
2009).
So is the audience really the driving force behind sharing or merely a filter that leads
people to share slightly different things depending on who they share with? More broadly, when
does the source (audience) play a relatively larger role in what people talk about?
Word-of-Mouth 45
There are likely a number of moderators. One may be audience size. As noted, because
narrowcasting (i.e., talking with one person) is more directed, it is driven more by the audience
and what will be useful to them (Barasch and Berger 2012). Another moderator may be arousal.
As mentioned, arousal may lead people to be more self-focused, and thus lead word-of-mouth to
be driven more by the sharer. The stage of the conversation may also matter. People may be
more focused on themselves when the conversation starts, but focus relatively more on others as
the conversation evolves and utterances are more in response to what the other person has said.
Evolution of Conversation
Most work on word-of-mouth treats each utterance as an isolated event, but in reality,
each utterance is embedded in a broader conversation. How do conversations evolve from one
topic to the next? What psychology underlies conversational evolution, and what types of things
may be more likely to be discussed at different stages of conversation?
Accessibility likely plays a big role in how conversations evolve. Just as conversation
partners or contextual factors can act as triggers, so can prior conversation topics, increasing the
accessibility of related ideas and making them more likely to be discussed. Thus conversations
may move from one cued topic to the next, along a line of related concepts.
Topics may likely become more personal, revealing, and abstract as the conversation
evolves. Particularly for strangers, but even for friends, talking for a period can create
familiarity and connection that encourages trust and deeper revelation (particularly when
conversation involves self-disclosure, Aron et al 1997). It is also difficult to start a conversation
with high-level issues or controversial topics (e.g., abortion or beauty norms in society).
Word-of-Mouth 46
Consequently, conversations may start with more concrete, pedantic topics and through
associated cues, move to broader more abstract higher-level discussions.
Word-of-mouth and Social Networks
Though a full review of social networks research is beyond the scope of this paper, it is
also important to consider how networks and word-of-mouth interact. Word-of-mouth can
inform and influence, but how it flows throughout a population depends on the pattern of social
ties (Brown and Reingen 1987; see Van den Bulte and Wuyts 2009; Watts 2004 for reviews). A
particular video may be highly sharable, but if it originates in a disconnected corner of the
network, it may be unlikely to ever become viral. Similarly, complex contagions may be more
likely to catch on if a group of tightly connected individuals are seeds, rather than if the product
is diffused across the network (Stephen and Berger 2012; Kalish, Mahajan, and Muller 1995).
Self-Report Biases
Whenever research involves asking people about their behavior, researchers must also
ask themselves whether participants’ responses are truly accurate. People often have little
insight into why they did something, and may be unaware of the stimulus that caused their
response and the fact that it impacted their behavior (Nisbett and Wilson 1977). Further, attitudes
do not always translate into behavior (Ajzen and Fishbein 1977) and misreporting may occur
even when people are asked about their actual behavior. Rather than reflecting reality, responses
may be based on implicit theories, social desirability, memory biases, and other factors.
These same issues should impact responses about word-of-mouth. Take questions about
prospective behavior. Researchers often ask people how likely they would be to talk about
Word-of-Mouth 47
different brands or stories. But given that people prefer to see themselves in a positive light, it
would not be surprising if people report being more likely to talk about things that make them
look good rather than bad (e.g., funny stories or helpful topics), even if that is not what they
would actually end up discussing. Indeed, people thought they would mention more interesting
brands in face-to-face discussion, even though more direct measures of behavior found that this
was not the case (Berger and Schwartz 2011).
Issues also affect questions about retrospective behavior. People’s responses about what
they talked about in the past are shaped by memory. People will be more likely to report talking
about things that stick out in memory, rather than things that don’t. So even if people are not
trying to self-enhance, they may remember talking about interesting things more than boring
ones because interesting discussions are more memorable (the same is true of more emotional
events). Most people talk a lot about meals for example, but retrospective surveys would not
show this because those conversations are unlikely to be striking enough to persist in memory.
This suggests that when self-enhancement is involved, studies that involve read behavior
may be particularly useful. Have participants engage in real conversations, pick things to talk
about, or even write to others expecting that they would actually converse. Even including just
one real behavior study in a paper provides some assurance that the phenomena studied is not
restricted to self-report. Otherwise, responses may be particularly biased towards selfenhancement and away from factors like accessibility or non-conscious process that may be hard
for people to anticipate in advance.
Word-of-Mouth 48
Thinking outside the Lab
The emergence of online word-of-mouth has provided a wealth of data to examine (Lazer,
et al. 2009). Tweets, online reviews, and blogs are only a few of the many “big data” sources of
real sharing behavior. Researchers have begun using text mining and natural language processing
to pull insights from large corpuses of written information (Ghose, Iperirotis, and Li,
forthcoming; Netzer, Feldman, Goldenberg, and Fresko 2012; Tirunillai and Tellis 2012). But
even less complex tools can be useful. Simple textual analysis programs (e.g., Linguistic Inquiry
and Word Count and ANEW) can shed light on a host of psychological processes (Pennebaker,
Mehl, and Niederhoffer 2003; also Berger and Milkman 2012; Chen and Lurie 2012). Others
have manually coded psychological constructs (Moore 2012; Schlosser 2011).
Researchers have also figured out clever ways to capture and analyze offline chatter
using small recording devices (Mehl, et al. 2001; Mehl and Robbins 2012) or transcripts of
customer service calls (Moore, Packard, and McFerran 2012). Others have devised field
experiments, creating online applications that allow randomization of different word-of-mouth
messages over time (Aral and Walker 2012; Centola 2011).
Laboratory experiments are vital for teasing out underlying mechanisms behind word-ofmouth. But by collecting field data, or running field experiments, researchers can examine the
relative importance of different process. Further, given that individuals may not always be aware
of what they talk about, or will talk about, measuring actual behavior may be particularly
valuable.
Word-of-Mouth 49
Conclusion
In conclusion, word-of-mouth is both frequent and important. But while researchers have
shown the consequences that word-of-mouth has on behavior, we have only barely begun to
understand its causes. What do people talk about, who they talk about it with, and what channel
do they talk about it through? These are only a few of the overarching questions that deserve
further research. Word-of-mouth is a multiply determined phenomenon. It is an interaction of
the source, the audience, the channel, and the content. Hopefully this review will spur more
researchers to delve into this exciting area.
Word-of-Mouth 50
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