Negative emotions in social media as a managerial challenge
Turku University of Applied Sciences
Abstract: The paper presumes that social media is an environment loaded with emotions. It has been
argued that companies should be aware of the emotional tone of social media discussions related to their
products, services and brands. Studies have shown that positive sentiment around a company’s brands in
social media often becomes reality in the balance sheet and on the bottom line. However, sometimes things
go wrong and a company find itself as a target of cyber protests. Studies have shown that social media is a
context where local and small events may escalate into bigger and even global ones in a very short period of
time. A great deal of social media behaviour is affected by negativity bias. In psychology, negativity bias
refers to a phenomenon in which humans have a greater recall of unpleasant memories compared to
positive memories. Adapting it to social media, it means that people are much more likely to recognise and
be influenced by negative information shared in social media. Based on the review of 43 academic journal
articles, the paper identifies six factors which should be taken into consideration in managing negative
emotional bursts in social media. The paper contributes to the research and practice of managing emotions
by increasing the understanding of the nature and consequences of negative emotions expressed and
shared in social media.
Keywords: Social media, Emotional intelligence, Negative emotion
Social media has become an integral part of life for many people. A great deal of social media content is
emotionally loaded. People express the highs and lows of their everyday life, establish new friendships and
break up old ones, share holiday and party pictures, praise and complain about brands, idolise the
achievements of their descendants and pets through different social media sites – behaviour which is
strongly affected by emotions. The paper presumes that emotions are the driving force for posting content
objects to Facebook, Twitter, Sina Weibo, VK, YouTube, Instagram, Pinterest and thousands of similar social
Emotion refers to an emotional state involving thoughts, physiological changes, and an outward expression
or behaviour. Emotions are expressed in facial reactions, gestures or postures and they are intuitively or
intentionally directed toward a certain target. (Cacioppo & Gardner, 1999.) Emotions are nowadays
recognised as important resources in managing organisations (Simon, 1987). Psychological literature
typically classifies emotions into two axes that describe their valence and arousal. Valence indicates whether
the affect related to an emotion is positive or negative, and arousal indicates the personal activity induced by
that emotion (Russel, 1980). Studies have found out that the valence and arousal of emotions is a useful
approach to categorise social media content, describe the behaviour and analyse the differences between
different users (Schweitzer & Garcia, 2010).
Many studies have argued that companies should be aware of the emotional tone of social media
discussions related to their products, services and brands (e.g. Tripp & Grégoire, 2011; Fan et al., 2013;
Rapp et al., 2013). It has been found out that mitigating negative sentiment and expanding positive
sentiment around a company’s brands in social media often becomes reality in the balance sheet and on the
bottom line (Noble et al., 2012; Hutter et al., 2013). At best, a company’s social media behaviour launches
positive electronic word-of-mouth (eWOM) – communication of positive statements made by potential, actual,
or former customers about a product or company, which is made available to a multitude of people and
institutions via the internet (Hennig-Thurau et al., 2004).
However, things can go wrong and a company can find itself as a target of protests in cyberspace. Studies
have shown that social media is a context where local and small events may escalate into bigger and even
global ones in a very short period of time (Tadic et al., 2013; Hemsley & Mason, 2013). Since social media is
not an alternative to real life, but it is part of it (Shirky, 2010), it is unavoidable that sometimes the behaviour
in social media is motivated by negative emotions. The paper presumes a negativity bias in social media
communication. This does not necessary mean that negative posts and comments outweigh positive ones in
numbers, but that negative emotion is more influential. In psychology, negativity bias refers to a
phenomenon by which humans have a greater recall of unpleasant memories compared to positive
memories. Adapting this to social media, it may mean that we are much more likely to recognise and be
influenced by the negative information. Perhaps negative information is contagious (cf. Berger, 2013).
Based on the above-mentioned, it is striking that, according to the best knowledge of the author, there is no
prior work which attempts to understand managing the challenges of negative emotions expressed and
shared in social media. This paper fulfils the research gap by systematically reviewing 43 academic journal
articles. The paper contributes to the research and practice of emotional intelligence by providing an
overview of prior literature on negative emotions in the context of social media.
2. Research design
By performing the literature review (Creswell, 2007) this paper integrates existing information and provides a
new insight for understanding the various aspects of negative emotions expressed and shared in social
media. Due to the heterogeneity of the studies reviewed, a meta-analysis (i.e. employing statistical and
econometric procedures for synthesising findings and analysing data, Transfield et al. 2003), was not
appropriate for this review. The analysis conducted was therefore descriptive and inductive by nature. The
literature review was conducted using Boolean searches in the following databases: ABI Inform ProQuest,
EBSCO, Elsevier Science Direct, and Emerald. The following search phrase was applied to all databases:
TITLE (“social media” OR “social network*” OR “online communit*” OR “web 2.0” OR “Facebook” OR
“Twitter”) AND FULL-TEXT (emotion OR feeling OR mood OR affect) AND (negative OR anger OR fear OR
sad* OR disgust* OR contempt OR shame* OR embarrass* OR frustrate* OR irritat* OR envious OR jealous
OR scar* OR panick* OR nervous OR worried OR tense OR depress* OR nostalg* OR guilt* OR miserable
OR humiliate*). The search was confined to peer-review journals. The search based on that definition was
conducted on January, 2014, and yielded 715 articles. In addition, as complementary data, the following
search phrase was applied to all databases: TITLE “internet” AND ABSTRACT “word-of-mouth”. The search
was conducted in February 2014, and yielded 198 articles.
The 913 articles were analysed as follows. Firstly, the abstracts of articles were read cursorily. Examination
of the abstracts reduced the number of articles to 43. In the second phase, the 43 articles were read in full by
the author and two other researchers involved in a research project called NEMO – Business Value from
Negative Emotions. The articles were analysed in terms of their subject matter, their theoretical framework,
their methodology, and empirical findings. The objective of this phase was to ensure that the studies were
relevant to the purpose of this paper. The articles were labelled with as many manifestations of negative
emotions as were identified in them. The third phase of the analysis consisted of reducing and combining the
manifestations of negative emotions. After several combining and restructuring cycles undertaken with the
help of mind mapping, a six-factor classification of negative emotions in the context of social media was
inductively compiled by the athor. The author verified the classifications with his research colleague and
borderline cases were discussed. The results of the literature review are presented in the third section.
Finally, conclusions are drawn in the fourth section.
3. Results: How and why negative emotions are expressed and shared in social media?
Based on the review of 43 academic journal articles, the paper identifies 6 themes which challenge
companies’ ability to act in an emotionally intelligent way in the social media age.
3.1 Demographic of sharing and expressing negative emotions
Demographic factors refer to a set of variables such as a given population’s age, gender and education,
which is expected to have consequences on behaviour. Consistent with previous research, the reviewed
literature hints that age and gender differences play a role in expressing and feeling negative emotions in
social media. The results can be summarised in four findings as follows: Firstly, young people tend to be
more emotionally vulnerable regarding to social media. Przybylski et al. (2013), for example, have found out
that compared to older people, the young feel fear of missing out – a pervasive apprehension that others
might be having rewarding experiences from which one is absent. In order to avoid missing out, young
people may have a compulsive need to be continually connected with what others are doing. Adapting
Nitzburg & Farber (2013), it seems that young people who tend toward disorganised and anxious attachment
styles are extremely dependent on social networking sites. Secondly, young people express more negative
emotions compared to older people. Young people’s tendency to express negative emotion has been
explained by puberty (Pfeil et al., 2009). Compared to young people, older people rely more on formal
communication mode. A bit surprisingly, Özgüven & Mucan (2013), however, have found opposite results.
According to them “bloggers over 50 were more like to use the blog as emotional outlet with a negative tone”
compared to their younger counterparts. Thirdly, gender does not predict whether the use of social media
creates negative emotions. It has been suggested that extensive online gaming is more typical among men
than among women increasing the odds of negative emotional consequences such as problems with partner,
work or education and health (Beutel et al., 2011). On the other hand, some studies argue that women are
vulnerable to feel negative emotions because of the content they expose themselves to in social media.
Thompson & Lougheed (2012), for example, have noticed that women suffer from stress more likely than
men, based on Facebook pictures. Women also feel anxious and upset if they cannot access Facebook.
Fourthly, men express more high arousal and women more low arousal negative emotions than their
opposite sexes. Lee (2012), for example, has found out that males use more comments associated with
anger than females, while females used more comments associated with sadness than their male
3.2 Culture of expressing and sharing negative emotions
Culture refers to the broad set of behaviours, norms and values that comprise an organisation, community or
society. The reviewed literature shows that cultural factors influence how social media is used in a particular
society. Cultural differences in social media use manifest in various forms. Berthon et al. (2012), for example,
have reminded that China and some other countries have banned the use of popular social networking sites
such as Facebook. It has also been suggested that online consumer behaviour, especially online word-of-
mouth, is shaped by cultural norms and values (Chu & Choi, 2011). Comparing American and Chinese social
media users, Chu & Choi (2011) found out that American users were more familiar with loose social
networks than their Chinese counterparts, who preferred tightly knit networks with close ties. As culture is the
guiding principle for people’s attitude and behaviour as well as relationships with others (Chu & Choi, 2011),
presumably culture generates differences in expressing and sharing negative emotions in social media.
However, a bit surprisingly the reviewed literature does not confirm any significant relationship between
national cultural differences and negative emotional expressions. Instead of a national cultural dimension,
reviewed studies imply that there are subcultures within the social media landscape which can be
emotionally shaped. Very concretely, this manifests negative and critical attitudes towards companies and
their products. There is no shortage of studies which argue that social media has changed the power
balance between an organisation and its stakeholders. One aspect of that change is consumers’ increased
ability to share negative information about organisations. Fournier & Avery (2011), for example, have found
out that “critical consumers networked together can wreak havoc on a brand”. Similarly, Park et al. (2012)
have pointed out that organisations are nowadays at risk of being the targets of negative sentiments
spreading rapidly in social media sites.
3.3 Object of expressing and sharing negative emotions
One of the central attributes of emotional experience is intentionality – i.e. an emotion has an object.
Generally objects can be different sorts of things, people, people’s behaviour, state of affairs and so on. In
this paper objects are divided into two categories: things, behaviour or state of affairs in real life and things,
behaviour or state of affairs in virtual world. Firstly, the reviewed literature includes several examples of
incidents in which something negative that has happened in real life has been shared in social media. Two
different types of negative emotional situations in real life were found: those which are independent of any
intentional actors and those which are induced by intentional actors. Physical illness, mental problems such
as anxiety and depression and a negative state of affairs, such as loneliness and boredom, are typical
examples of independent and real life situations in which people share their negative feelings in social media
(Morahan-Martin & Schumacher, 2003; Bell, 2007; Caplan, 2010; Gencer & Koc, 2012; Przybylski et al.,
2013). The rationale behind such behaviour may be that people who use social media in order to share their
dissatisfaction and negative emotions may benefit from feeling that they are connected by helping and
supporting others (Ziebland & Wyke, 2012). Dissatisfaction for product or service quality is a typical example
of dependent real life situations in which people go to social media to express and share their negative
feelings. Customers are nowadays keen to spread the message of dissatisfaction as wide as possible. A
negative customer experience in a brick-and-mortar shop can become an issue in social media at lightning
speed. The above-mentioned two behaviours implicitly rest on the idea that the pace of life online and offline
has become increasingly intertwined (Przybylski et al., 2013). Secondly, however, the reviewed literature
suggests that social media has created a virtual world with its own logic. From the perspective of negative
emotions, this comes clear in rant-sites, which are dedicated to dispersing negative information related to
organisations’ behaviour or bad product/service experiences. Martin et al. (2013), for example, have
explained the existence of rant-sites by saying that individuals who posted negative information on rant-sites
feel relaxed after venting. In a similar vein, anti-brand hate sites have been seen to offer people a venue for
expressing negatively biased content (Kucuk, 2008).
As social media has become a larger part of everyday life, it has also generated new emotionally driven
threats, such as the ethical use of social media user data. Social media enables tracking and analysing the
data gathered from different social media sites. From the organisational perspective, social analytics can be
used, for example, in improving customer segmentation and targeting. The more accurate picture of
customers’ behaviour, the more effective the marketing. Likes, tastes and preferences are turned into
searchable things with monetary value (Sampson, 2012). However, people are getting more and more
concerned about their privacy. The reviewed studies imply that social analytics is a sensitive activity. If it is
done too “well”, people may fight back. This is because people feel that organisations violate their “right to be
alone” (Warren & Brandeis, 1890). Several studies have suggested that individuals’ privacy is under threat
on social media sites because they deliberately or inadvertently disclose too much information about
themselves (Lewis et al., 2008; Livingstone, 2008; Fogel & Nehmad, 2009). Presumably this generates
negative emotions, such as fear, annoyance and even anger.
3.4 Platforms of expressing and sharing negative emotions
Social media refers to a constellation of shared technologies that derive their value from the participation of
users through directly creating original content, modifying existing material, contributing to a community
dialogue and integrating various media together to create something unique (Tapscott & Williams, 2007).
Based on the reviewed literature, it seems that different social media sites differ in their ability to induce
expressing and sharing negative emotions. Leung (2013), for example, has found out that Facebook is not
the channel of choice for venting negative feelings. Leung explains this by saying that Facebook (and similar
social networking sites) is a platform for keeping in touch with friends, sharing and seeing updates, not a
place for voicing conflicting views. When people want to display negative emotions and voice conflicting
views, they prefer blogs and forums (Leung, 2013). Differences between social media sites in venting
negative feelings can also be addressed by anonymity. It has been argued that anonymity makes people
more honest in sharing their negative experiences online (Yun & Park, 2011; Verhagen et al., 2013). Social
media sites which enable anonymity make expressing negative issues safer to individuals, “as they cannot
be identified as the perpetrators of certain actions or behaviors” (Lapidot-Lefler & Barak, 2012). This may
provoke toxic behaviour, such as impulsive and aggressive cyber-bullying and off-topic and off-colour
comments (Kietzmann et al., 2011). It has been predicted that mobile use of social media will grow rapidly.
According to one survey, two thirds of people were reported to use social media via mobile devices (Social
Media Frontiers, 2013). Smart phones and tablets transform our communication behaviour. The reviewed
studies show – although not very strongly (probably due to the novelty of the phenomenon) – that mobile
devices potentially influence the ways we express and share emotions (Kwon et al., 2013). Goh et al. (2009),
for example, have found out that mobile devices equipped with cameras enable behaviour that meets
emotional needs. One can expect that mobile devices have increased the possibilities for instant reporting in
both good and bad.
3.5 Motivation to express and share negative emotions in social media
People express negative emotions in social media for a number of reasons. Based on the reviewed
literature, four motivations have been identified. Firstly, people ventilate for themselves. Thogersen et al.
(2009) and Verhagen et al. (2013), for example, have found that consumers use negative eWOM for drawing
attention to their dissatisfaction in order to get a solution or compensation. In addition to getting concrete
compensation, people ventilate because it helps to reduce their anger induced by bad experiences or a
negative state of affairs (Martin et al., 2013). Posted rants may act as catharsis in the sense that people feel
calm and relaxed after ranting (ibid.). In addition, Hadert & Rodham (2008) have found out that the active
online processing of one’s emotions is beneficial in “terms of emotional well-being, reductions in self-
reported symptoms and improvements in mood”. Secondly, consumers ventilate for altruistic reasons,
particularly helping others. This is the case when people disclosure their negative experiences in order to
prevent others from suffering a similar incident (Litvin et al., 2008; Parra-López et al., 2011). Adapting Lee et
al. (2012) it seems that when people browse consumer created content, they are “likely to expect intrinsic
motives of altruism”. Sharing negative experiences online is advantageous because negative information is
more diagnostic than positive information when making decisions (Jones et al., 2009). It means that
information about a product that does not work as it should is more diagnostic than information about a
product that does work as it should. Thirdly, consumers ventilate to help companies to improve their
performance. Zaugg & Jäggi (2006), for example, have identified that consumers complain “to assure that
the issue is structurally solved”. Although negative in tone, this kind of complaining behaviour can be
extremely beneficial to companies. This is because it reflects consumers’ engagement with the organisation.
Hanna et al. (2011), for example, have suggested that companies should aim to promote consumers to talk
about their products and service in social media. Although it may be dangerous and risky, it is in the interest
of companies to be open for social media conversations (Kietzmann et al., 2011). Communication about
brands happens, whether companies like it or not. Fourthly, negative emotions are expressed in social media
motivated by individuals’ need for publicity and attention. As peculiar it may sound, some individuals
energise themselves by sharing negative and detrimental information. Noble et al. (2012) have labelled
these individual as trolls. Troll is an individual who shares “inflammatory, extraneous or off-topic messages
[…] in social media, with the primary intent of provoking readers into an emotional response or of otherwise
disrupting normal on-topic discussion”. Contrary to a dissatisfied customer, it is in the troll’s deliberate
intention to damage an organisation or a community.
3.6 Dynamics of sharing negative emotion in social media
Consistently with the old saying “birds of a feather flock together”, the reviewed literature suggests that
incidents and events with negative emotions generate a special dynamic. Popular social media users have
an effect on their audiences’ moods (Bae & Lee, 2012). Metaphorically, it has been suggested that negative
emotions constitute avalanches (Tadic et al., 2013). Tadic et al. (2013) have found out that negative emotion
valence leads to the occurrence of larger and longer living avalanches than positive emotions. Presumably,
the feature of social media that allows a particular post to be available to everyone immediately increases
the odds of emotional bursts (Schweitzer & Garcia, 2009). Social media enables people to talk to one
another and therefore multiplies the ability to express negative experiences. Avalanches and negative
eWOM originate from the same roots: a myriad of interactions between connected users bring about a chain
of events that progress non-linearly. From the perspective of negative emotions, the significance of
interactions promoted by social media lies in that they enable the multiplication of small influential changes.
That is to say that social media has the potential to increase the non-linear characteristics of interaction
(Tadic et al., 2013). Due to nonlinearity, the direction, velocity and intensity of avalanche originated by
negative experience is unpredictable. What is known is that social media enables two processes:
globalisation of local events and localisation of global events. Within social media there is no lack of
examples of how locally felt negative experience has transformed into a global issue. As Berthon et al.
(2012) have put it: “in the age of social media, local events seldom remain local […] and general issues
seldom remain general”. The result is something which can be called as emergent. Emergence results from
the processes where each individual continually decides with which other actors it will engage, and what
emotion it will share with them. Emergence displays properties which cannot be traced back to individual
contributions (Schweitzer & Garcia, 2010). The inflow of negative emotions can lead to the emergence of
patterns of themes which no individual could have decided. Seemingly, things just happen without a
particular reason. An emergent collective negative emotion differs from individual negative emotion in terms
of quantity and quality.
Metaphorically, social media punctures holes into organisations’ walls, making them transparent in an
unforeseen way. One striking aspect of transparency is that organisations are forced to face emotionally
rationalised criticism and complaints. When something negative happens, organisations cannot exclude the
possibility that it will be reported in social media. Presumably, the rapid growth of mobile use of social media
will increase the odds that negative experiences are expressed and shared in the virtual world. This paper
has identified six factors which can be used in “managing” negative emotional bursts in social media.
“Managing” is in quotation marks, because the acts of expressing and sharing negative emotions in social
media cannot be managed in a strict manner. What is needed is the understanding of how to behave
emotionally intelligently in social media. The message is clear: an emotionally intelligent organisation (cf.
Goleman, 1995) must develop the ability to recognise the emotions shared and diffused in social media, and
to understand their meaning for the business and to behave on the basis of that understanding.
As a general conclusion, the paper proposes that organisations should be aware of the tone of social media
discussions. A critical aspect of the awareness is a quick identification of the seeds of potential emotional
bursts. Obviously this is not an easy task, because of the huge amount and variety of social media content
provided by billions of social media users on thousands of different social media sites. However, something
can and should be done. This paper proposes two managerial implications. Firstly, organisations should use
robust techniques to monitor social media discussion. One potential approach to this is sentiment analysis.
Sentiment analysis refers to identifying the polarity of sentiment presented in unstructured text, in order to
identify whether the expressions indicate positive, neutral, or negative valence toward the subject (Pang &
lee, 2008; Bae & Lee, 2012). Technically sentiment analysis can be done various ways, such as lexicon-
based analysis or machine learning methods. The crucial thing is that sentiment analysis enables
organisations to act before negative emotions are spread through social media. Secondly, and perhaps more
fundamentally, organisations should understand the potentially positive consequences of negative emotions
expressed and shared in social media. For example, when negative emotions reflect bad product or
customer experience they should not be seen as threat but as important inputs for the organisation’s
development. Adapting Hirschman’s (1970) “exit–voice” theory, an emotionally disappointed customer is
voicing his/her opinion about the subject he/she is engaged with. It is in the organisation’s interest to enable
its customers to use their voice instead of exit. As shown in several studies within consumer behaviour
research, a complaining customer is not necessarily a former customer. Quite the contrary, this paper
hypothesises that social media helps organisations to map negatively motivated customers and encounter
them in a way which increases – not decreases – customer loyalty. If negative experiences are treated
properly, complaining customers can even become companies’ fans.
Nonetheless, due to the heterogeneity of the reviewed studies (some of them were psychologically while
others technologically or organisationally focused) the categorisation of negative emotions into six themes is
indicative, not explanatory. Therefore, in order to understand the mechanisms of transforming negative
emotions into useful resources require more empirical research which focuses exclusively on negative
emotions relevant in the organisational context.
Bae, Y. & Lee, H. (2012) ”Sentiment analysis of twitter audiences: Measuring the positive or negative
influence of popular twitterers”, Journal of the American Society for Information Science & Technology,
Bell, V. (2007) “Online information, extreme communities and internet therapy: Is the internet good for our
mental health?”, Journal of Mental Health, 16(4), 445–457.
Berger, J. (2013) Contagious – Why things catch on, Simon & Schuster, London, UK.
Berthon, P. R., Pitt, L. F., Plangger, K. & Shapiro, D. (2012) “Marketing meets Web 2.0, social media, and
creative consumers: Implication for international marketing strategy”, Business Horizons, 55(3), 261–271.
Beutel, M. E. & Brähler, E., Glaesmer, H., Kuss, D., Woftling, K. & Müller, K. W. (2011) “Regular and
problematic leisure-time internet use in the community: Results from a German population-based survey“,
Cyberpsychology, Behavior, and Social Networking, 14(5), 291–297.
Cacioppo, J. T. & Gardner, W. L. (1999) “Emotion”, Annual Review of Psychology, 50, 191–214.
Caplan, S. E. (2010) ”Theory and measurement of generalized problematic Internet use: A two-step
approach”, Computers in Human Behavior, 26(5), 1089–1097.
Chu, S-C. & Choi, S. M. (2011) ”Electronic Word-of-Mouth in Social Networking Sites: A Cross-Cultural
Study of the United States and China”, Journal of Global Marketing, 24(3), 263–281.
Creswell, John (2007) "Review of the Literature", Chapter 2 of Research Design: Qualitative, Quantitative,
and Mixed Method Approaches. Thousand Oaks: Sage Publications.
Fan, L., Zhang, Y., Dang, Y. & Chen, H. 2013, "Analyzing sentiments in Web 2.0 social media data in
Chinese: experiments on business and marketing related Chinese Web forums", Information Technology and
Management, 14(3), 231–242.
Fogel, J. & Nehmad, E. (2009) “Internet social network communities: Risk taking, trust, and privacy
concerns”, Computers in Human Behavior, 25, 153–160.
Fournier, S. & Avery, J. (2011) “The uninvited brand”, Business Horizon, 54(2), 193–207.
Gencer, S. L. & Koc, M. (2012) ”Internet Abuse among Teenagers and Its Relations to Internet Usage
Patterns and Demographics”, Journal of Educational Technology & Society, 15(2), 25–36.
Goh, D. H-L-, Ang, R. P., Chua, A. Y. K. & Lee, C. S. (2009) “Why We Share: A Study of Motivations for
Mobile Media Sharing”, Active Media Technology Lecture Notes in Computer Science, 5820, 195–206.
Goleman, D. (1995) Emotional Intelligence, Bantam Books.
Hadert, A., Rodham, K. (2008) ”The invisible reality of arthritis: A qualitative analysis of an online message
board”, Musculoskeletal Care, 6(3), 181–196.
Hanna, R., Rohm, A. & Crittenden, V. L. (2011) “We´re all connected: The power of the social media
ecosystem”, Business Horizons, 54, 265–273.
Hemsley, J. & Mason. R. M. (2013). “Knowledge and knowledge management in the social media age”,
Journal of Organizational Computing and Electronic Commerce, 23(1-2), 138–167.
Hennig-Thurau, T., Gwinner, K. P., Walsh, G. & Gremler, D. D. (2004) "Electronic word-of-mouth via
consumer-opinion platforms: What motivates consumers to articulate themselves on the Internet?", Journal
of Interactive Marketing, 18(1), 38–52.
Hirschman, A. O. (1970) Exit, Voice, and Loyalty: Responses to Decline in Firms, Organizations, and States.
Harvard University Press, Cambridge, MA.
Hutter, K., Hautz, J., Dennhardt, S. & Füller, J. 2013, "The impact of user interactions in social media on
brand awareness and purchase intention: the case of MINI on Facebook", The Journal of Product and Brand
Management, 22(5), 342–351.
Jones, S. A., Aiken, K. D. & Boush, D. M. (2009) “Integrating Experience, Advertising, and Electronic Word of
Mouth”, Journal of Internet Commerce, 8(3/4), 246–267.
Kietzmann, J. H., Hermkens, K., McCarthy, I. P. & Silvestere, B. S. (2011) “Social media? Get serious!
Understanding the functional blocks of social media”, Business Horizons, 54(3), 241–251.
Kucuk, S. U. (2008) “Negative Double Jeopardy: The role of anti-brand sites on the internet”, Brand
Management, 15(3), 209–222.
Kwon, O, Kim, C-R., Kim, G. (2013) ”Factors affecting the intensity of emotional expressions in mobile
communications”, Online Information Review, 37(1), 114–131.
Lapidot-Lefler, N. & Barak, A. (2012) ”Effects of anonymity, invisibility, and lack of eye-contact on toxic online
disinhibition”, Computers in Human Behavior, 28(2), 434–443.
Lee, C. S. (2012) “Exploring emotional expressions on YouTube through the lens of media system
dependency theory”, New Media & Society, 14(3), 457–475.
Lee, D., Kim, H., & Kim, J. K. (2012) ”The role of self-construal in consumers’ electronic word of mouth
(eWOM) in social networking sites: A social cognitive approach”, Computers in Human Behavior, 28(3),
Leung, L. (2013) “Generational differences in content generation in social media: The roles of the
gratifications sought and of narcissism”, Computers in Human Behavior, 29(3), 997–1006.
Lewis, K., Kauffman, J., & Christakis, N. (2008) “The taste for privacy: An analysis of college student privacy
settings in an online social network”; Journal of Computer-Mediated Communication, 14, 79–100.
Litvin, S. W., Goldsmith, R. E. & Pana, B. (2008) ”Electronic word-of-mouth in hospitality and tourism
management”; Tourism Management, 29, 458–468.
Livingstone, S. (2008) “Taking risky opportunities in youthful content creation: Teenagers’ use of social
networking sites for intimacy, privacy and self-expression”; New Media Society, 10, 393–411.
Martin, R. C., Coyier, K. R., van Sistine, L. M. & Schroeder, K. L. (2013) “Anger on the Internet: The
Perceived Value of Rant-Sites”, CyberPsychology, Behavior & Social Networking, 16(2), 119–122.
Morahan-Martin, J. & Schumacher, P. (2003) ”Loneliness and social uses of the Internet”, Computers in
Human Behavior, 19 (6), 659–671.
Nitzburg, G. C. & Farber, B. A. (2013) “Putting up emotional (Facebook) walls? Attachment status and
emerging adults´ experiences of social networking sites”, Journal of Clinical Psychology: In Session, 69(11),
Noble, C. H., Noble., S. M. & Adjei, M. T. (2012) “Let them talk! Managing primary and extended online
brand communities for success”, Business Horizons, 55, 475–483.
Pang, B. & Lee, L. (2008) “Opinion mining and sentiment analysis”, Foundations and Trends in Information
Retrieval, 21(1–2), 1–135.
Park, J., Cha, M., Kim, H. & Jeong, J. (2012). Managing bad news in social media: A case study on
Domino’s Pizza crisis. Proceedings of the 6th AAAI Conference on Weblogs and Social Media, 282–289.
Parra-López, F., Bulchand-Gidumal, J., Gutiérrez-Tano, D. & Díaz-Armas, R. (2011) “Intentions to use social
media in organizing and taking vacation trips”, Computers in Human Behavior, 27, 640–654.
Pfeil, U., Arjan, R. & Zaphiris, P. (2009) “Age differences in online social networking – A study of user profiles
and the social capital divide among teenagers and older users in MySpace“, Computers in Human Behavior,
Przybylski, A. K., Murayama, K., DeHaan, C. R: & Gladwell, V. (2013) “Motivational, emotional, and
behavioral correlates of fear of missing out”, Computers in Human Behavior, 29, 1841–1848.
Rapp, A., Beitelspacher, L.S., Grewal, D. & Hughes, D.E. 2013, "Understanding social media effects across
seller, retailer, and consumer interactions", Academy of Marketing Science Journal, 41(5), 547–566.
Russell, J. A. (1980) “A circumplex model of affect”, Journal of Personality and Social Psychology, 39(6),
Sampson, T. (2012) Virality. Contagion Theory in the Age of Networks, Minnesota: University of Minnesota.
Schweitzer, F. & Garcia, D. (2010) “An agent-based model of collective emotions in online communities”,
European Physical Journal B -- Condensed Matter, 77(4), 533–545.
Shirky, C. (2010) Cognitive surplus – Creativity and generosity in a connected age, The Penguin Press, New
Simon, H. A. (1987) “Making management decision: the role of intuition and emotion”, The Academy of
Management Executive, 1(1), 57–64.
Social Media Frontiers (2013) “Mobile marketing – Using social media on mobile phones”
Tadić, B., Gligorijević, V., Mitrović, M. & Šuvakov, M. (2013) ”Co-Evolutionary Mechanisms of Emotional
Bursts in Online Social Dynamics and Networks”, Entropy, 15(12), 5084–5120.
Tapscott, D. & Williams, A. D. (2007) Wikinomics: How Mass Collaboration Changes Everything,
Portfolio/Penguin, Toronto, ON.
Thogersen, J., Juhl, J. J. & Poulsen C. S: (2009) ”Complaining: A function of attitude, personality, and
situation”; Psychology & Marketing, 26(8), 760–777.
Thompson, S. H. & Lougheed E. (2012) “Frazzled by Facebook? An exploratory study of gender differences
in social network communication among undergraduate men and women”, College Student Journal, 46(1)
Transfield, D., Denyer, D. & Palminder, S. (2003) “Towards a methodology for developing evidence informed
management knowledge by means of systematic review”, British Journal of Management, 14, 207–
222.Tripp, T.M. & Grégoire, Y. (2011) "When Unhappy Customers Strike Back on the Internet", MIT Sloan
Management Review, 52(3), 37–44.
Zaugg, A. & Jäggi, N. (2006) “The impact of customer loyalty on complaining behavior”, in Isaís, P., Nunes,
M. B. & Martínes, I. J. (eds.) IADIS International Conference WWW/Internet, 119–123, Murcia, Spain.
Ziebland, S. & Wyke, S. (2012) ”Health and Illness in a Connected World: How Might Sharing Experiences
on the Internet Affect People's Health?”, Milbank Quarterly, 90(2), 219–249.
Özgüven, N. & Mucan, B. (2013) ”The relationship between personality traits and social media use”, Social
Behavior and Personality, 41(3), 517–528.
Verhagen, T., Nauta, A. & Feldberg, F. (2013) „Negative online word-of-mouth: Behavioral indicator or
emotional release?”, Computers in Human Behavior, 29, 1430–1440.
Warren, S. & Brandeis, L. (1890) “The right to privacy”, Harvard Law Review, 4, 193–220.
Yun, G. W. & Park, S.-Y. (2011) ”Selective posting: Willingness to post a message online”, Journal of
Computer-Mediated Communication, 16, 201–277.