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Social media – An arena for venting negative emotions

Authors:
SOCIAL MEDIA AN ARENA FOR VENTING NEGATIVE EMOTIONS
Harri Jalonen
Dr, Adjunct professor, Turku University of Applied Sciences, Finland
E-mail: harri.jalonen@turkuamk.fi
Phone: +358 44 907 4964
Abstract
Social media is seen as transforming into a global multiplier through which emotional experiences are shared and
strengthened. The essential factor in the ongoing transformation is that although emotions are felt on an individual
level, in social media they can simultaneously be shared with and by others. Many studies have shown that social
media is an arena for sharing information that reflects negative emotions. The theme of the paper is important as
nowadays people have access to online discussions, blogs and even websites devoted entirely to sharing negative
emotional experiences. After reviewing the literature, the paper explores and discusses the implications of negative
emotions shared in social media. The main contribution of the paper is the anatomy of the diffusion of collective
negative emotion in social media. In addition, the paper discusses the positive consequences of negative emotions
from an organisation’s perspective.
1. INTRODUCTION
Social media has changed the behavior inside and outside the organisation. It has provided new
opportunities and posed new threats. A positive interpretation of social media draws on the thought that
social media has provided new possibilities to the internal use of external knowledge as well as to the
external exploitation of internal knowledge. This has meant significant improvements particularly in
leadership, innovation management, knowledge management, marketing communication, and customer
service. Studies have shown that social media has made organisations transparent in unparalleled way. In
addition to positive and anticipated consequences, it has also been identified side-effects effects such as
the loss of control and power to manage organisation´s public image (Li & Bernoff, 2011). The more
open and social organisations has become, the more vulnerability they has become too (Mangold &
Faulds, 2009). The odds of brand insults and the loss of confidential information have increased
tremendously. Ironically, it may also happen as Denyer et al. (2011) have pointed out that social media
can be used for political purposes by managers implying that social media is no more ‘social’, ‘open’ or
‘participatory’ than other communication methods.
Social media is creeping into many aspects of our lives. A bit pointedly, it can be argued that many
behaviors that sociologists study are nowadays taking place in online. Social media is not an alternative to
real life, but it is part of it. Social media is still relatively new phenomenon which consequences cannot
be fully predicted. However, some sophisticated guesses can be made. The one is that behaviour in social
media contradicts with the theory of gatekeeping. According to the theory which was originally
developed by Kurt Lewin (1943), gatekeeping is the process through which information is filtered for
dissemination. Every medium has gatekeepers, who select and confine the information flows. Reporters,
for example, decide which sources are chosen to include in a story, whereas editors decide whether stories
are printed or covered. In contrast to traditional mass communication, social media is unregulated context
allowing ordinary people to publish almost anything that come to their minds. There is no need room for
gatekeepers in social media. Unsurprisingly, many studies have shown that social media is an arena for
sharing information that reflects negative emotions (e.g. Lapidot-Barak-Lefler & Barak, 2012; Hughes et
al., 2012; Lee & Cude, 2012).
The study focusing on collective negative emotions in social media is important because people have
nowadays access to online discussions, blogs and even Web sites devoted entirely to sharing negative
emotional experiences (Jones, 2009). Whether that mirrors “information democracy” (Sawhney & Kotler,
2001) or not, a possibility to ventilate feelings online poses a huge challenge for organisations.
Upon reviewing the literature, the paper explores and discusses the implications of negative emotions
shared in social media. The paper proposes the anatomy of the diffusion of collective negative emotion in
social media. In addition to detrimental consequences, it is supposed that negative emotions may have
positive effects.
2. SOCIAL MEDIA AND COLLECTIVE EMOTION
Social media refers herein to a constellation of Internet-based applications 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; Kaplan & Haenlein, 2010). Emotion is defined as feeling state involving thoughts and
physiological changes, outward expressions such as facial reactions, gestures or postures (Brehm, 1999;
Cacioppo & Gardner, 1999). Emotion has an object at which it is intuitively or intentionally directed
(Ibid.). Adapting Bar-Tal et al. (2007) and Schweitzer & Garcia (2010), the paper focuses on collective
emotions, which are shared by large number of individuals who are not necessarily members of the same
group or society. Collective emotions can display new properties, which are more (or less) than the
aggregation of emotions felt by individuals. The paper adopts the view that textual communication can
used for evaluating emotions (cf. Jansen et al., 2009; Chmiel et al., 2011). Social media posts are seen
acts which are, at least, partly induced by emotions.
Psychological literature typically classifies emotions into two axes that describe their valence and arousal
(Fig. 1). 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; Schweitzer & Garcia, 2010).
‘Astonished’ is positive emotion that encourages action, whereas ‘satisfied’ although with positive
valence discourages action. ‘Annoyed’ refers to negative emotion that encourages action, whereas
‘disappointed’ means negative emotion that discourages action. The focus of this paper is primarily on
emotions with negative valence and positive arousal.
Figure 1. A circumplex model of affect (adopted from Russell, 1980).
Social media has provided organisations new ways to communicate (publish and share content),
collaborate (collectively create content), connect (network with other people and organisations), complete
(describing, adding or filtering information, tagging contents and showing a connection between contents)
and combine (mixing and matching contents) (Vuori, 2011). Social media extends organisations creating
new possibilities to engage with stakeholders both internally and externally. Through social media,
organisations can acquire inspiration from their customers, suppliers and other stakeholders. Social media
can also be used for getting to know consumer´s preferences and testing the ideas that are being
developed within the organisation before their launch on the market.
Figure 2. Social media changes organization internally and externally.
From this paper´s perspective, the most interesting is that social media enables direct two-way interaction
not only between organisation and customers but also within customers. It has been argued that marketing
for the Facebook generation demands both thinking and acting differently (Meadows-Klue, 2008). The
need for change holds true also within organisation as the distance between the manager and subordinate
has shortened dramatically. This paper suggests that social media forces organisations behave in a way
which inspires its people and customers emotionally. Kieztmann et al. (2011), for example, have
suggested that organisations should identify employees who can create content that is “emotionally
appropriate for the community”. Adapting Rubin (2011) social media is seen transforming into “one big
global amplifier through which emotional experience is transmitted and strengthened”. The essential thing
is that although emotions are felt on an individual level, in social media they can simultaneously be
shared to and by the others. This has wide range of “real life” consequences. It has been shown that
social, political, cultural and economic events are correlated with Twitter mood levels. Similarly, Gilbert
& Karahalios (2010) have found out that anxious expressions in social media could predict downward
pressure on the S&P 500 index.
3. NEGATIVITY BIAS IN EMOTIONS AND ONLINE BEHAVIOR
It remains debatable whether the content of social media is more positive or negative. Previous studies
paint a contradictory picture. Robertson et al. (2013), for example, have found out that there are more
negative messages than positive ones in social media. Thelwall et al., (2010), among others, have come to
opposite conclusion. According to their study of MySpace messages, two-thirds of messages have
positive tone, and only one-thirds was negative.
Although there is no natural law, which proclaims that negative emotional experiences dominate social
media, however, this paper assumes that negative emotional experience and particularly its diffusion in
the community is based on logic which is different than in case of positive emotional experience. This is
because of negativity bias. Psychological studies have shown that negative experience, or fear of bad
events has a greater impact on people than do neutral or positive experiences (Baumeister et al., 2001).
Studies have also shown that negative events grow more rapidly with space or time than positive events.
This implies that negative emotions are more contagious than positive ones (Rozi & Royzman, 2001).
Negativity bias in online behaviour has been identified in a number of studies which has focused on
electronic word-of-mouth (eWOM). eWOM refers to a “statement made by potential, actual, or former
customers about product or company, which is made available to a multitude of people and institutions
via the Internet” (Hennig-Thurau et al., 2004). Lee & Cude (2012), for example, have found out that
consumers are very likely to use Internet as a mean to express their dissatisfaction. The stronger impact of
negative eWOM compared to positive eWOM has been explained by arguing that negative information is
more diagnostic than positive information in terms of cognitive judgement and decision making (Jones,
2009; originally Herr et al., 1991).
4. THE ANATOMY OF THE DIFFUSION OF COLLECTIVE NEGATIVE EMOTION IN
SOCIAL MEDIA
The paper views diffusion as the process in which an idea, thought or concept is communicated through
certain channels over time among the members of the social system (cf. Rogers, 2003). Instead of one-
way and linear process, it is assumed that the diffusion is a two-way and complex process in which
members involved affect to others and are being affected by others.
“United Breaks Guitar” (UBG) is probably one of the most popular examples of how negative emotional
experience can be diffused through social media. UBG is the song made and posted a YouTube by David
Caroll and his band Sons of Maxwell. It tells a story of how United´s baggage handling broke Caroll´s
guitar and how United refused to compensate the losses. The musical video was embedded into popular
BoingBoing blog whereafter it was given credit in Twitter community. After two weeks the musical video
was downloaded over 3.5 million times. (Hemsley & Mason, 2013).
This paper suggests that the UBG case is not an exception but a prevailing reality. It is expected that
despite of differences in nuances, UBG and similar incidents follow certain logic. Perhaps it is possible to
reveal the anatomy of the diffusion of collective negative emotion in social media.
A literature review of previous studies implicates six attributes of diffusion of collective negative emotion
in social media: 1) reasons to ventilate negative emotion, 2) clusterization of negative emotion, 3)
globallocal interplay, 4) nonlinear feedback, 4) possibility to anonymity, 5) key complainers, and 6)
emergent result.
Reasons to ventilate negative emotion
People express negative emotions online for a number of reasons. In consumer behavior research three
reasons have identified (Verhagen et al., 2013). Firstly, consumers ventilate for themselves. Thogersen et.
al., (2009) have found that consumers use negative eWOM for drawing attention to their dissatisfaction in
order to get solution or compensation. Secondly, consumers ventilate for helping others. This is 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). Thirdly, consumers ventilate for helping company
to improve their performance. Zaugg & Jäggi (2006), for example, have identified that consumers
complain “to assure that the issue is structurally solved”. It has also been suggested that sometimes people
run to rant-sites for venting anger (Martin et al., 2013). Posted rants may act as catharsis in sense that
people feel calm and relaxed after ranting (ibid.). Adapting Russell’s circumplex model all above
mentioned reasons for ventilating represent behavior which is motivated by emotionally negative valence
and positive (encouraging) arousal.
Clusterization of negative emotions
Instead of isolated experiences, what matter is their clusterization. Clusterization of emotion refers herein
to transformation of individual emotional states into cluster emotional states. Many studies imply that
emotion can bring people together. Bae & Lee (2012), for example, have found that the behavior of
popular Twitter users have an effect on their audiences’ moods. Metaphorically, clusterized emotions
constitute avalanches (Tadic et al., 2013) and groundswells (Bernoff & Li, 2008), which may have
detrimental effects on organisations. “United Breaks Guitar” music video was a negative avalanche which
hit the United Airlines. The root cause was mishandling of instrument, however, in order to become an
issue what was needed was other individuals’ contributions in terms of tweets, blog posts, comments etc.
Consistently with the negativity bias, Tadic et al. (2013) have found out that negative emotion valence
leads to the occurrence of larger 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).
Globallocal interplay
Social media’s statistic is impressive. By the beginning of 2014, the number of users of popular social
media sites is counted in hundreds of millions. The leading social media site, Facebook, has gathered
1200 million users in ten years. Microblogging service Twitter has attracted over 500 million users since
its foundation in 2006. Even more rapidly has grown in 2009 founded instant messaging service
WhatsApp, which has claimed to have over 400 million active users. Sina Weibo, China´s biggest social
media site has gathered over 500 million users. Vkontake, popular social networking site in Eastern
Europe, particularly in Russia, is also growing rapidly having nowadays over 200 million users.
The numbers of users, even though impressive, is not the issue. Crucial thing is that a huge number of
users enable two processes: globalization of local events and localization of global events. Within social
media there is no lack of examples of how locally felt negative experience has transformed global issue.
“United Breaks Guitar” case and many similar incidents have shown that, in the age of social media, what
is local almost inevitably becomes global, whether the organisation wishes it to or not. The power has
been taken from organisations by the individuals and communities that create, share, and consume blogs,
tweets, and so forth (Kietzmann et al., 2011). The same obviously holds also true for opposite direction.
An incisive example is the discussion about the wholesome and safety of the gene manipulated food. It is
a global issue, which influences customer behaviour in local level. Twin forces of globalism and localism
are induced by the very nature of social media which removes time delays and physical distance.
Nonlinear feedback
Social media could be an effective form of two-way communication as it: “potentially closes the feedback
loop, or makes the loop smaller if you like, because it makes it easier for people to understand how they
can give their feedback” (Denyer et al., 2011). Feedback processes are non-linear i.e., minor changes
can produce disproportionately major consequences and vice versa. Feedback processes multiply the
connectivity inside and outside the organisation. A circular dependency relationship is typical of feedback
processes: this means that the result of the previous situation is the stake in the following one. In other
words, what has happened before is included, and continues, in what happens later. Many authors in the
field of social media have emphasised that most organisations have no choice: they cannot remain non-
participants, because their customers and other stakeholders participate anyway. Social media enables
customers to talk to one another and therefore multiplies the ability to express negative experiences (tähän
lähteitä). Avalanche, groundswell and eWOM originate from the same roots: a myriad of local
interactions between individuals bring about a chain of events that progress non-linearly. From the
perspective of negative emotions, the significance of the feedback processes promoted by social media
lies in that they enable the multiplication of small influential changes. 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/groundswell originated by negative experience is
unpredictable.
Possibility to anonymity
Many social media sites allow anonymous “freedom of speech”. Naturally this freedom can be used both
for good or bad. Yun & Park (2011) and Verhagen et al. (2013) have identified different consequence of
online anonymity. According to them anonymity makes people more honest in sharing their negative
experiences online. This is because Internet prevents people from facing any social consequences. Derks
et al. (2004), for example, have suggested that anonymity creates deindividuation and may lead to
antinormative behaviour. Anonymity is considered a major factor of “disinhibitive behaviour” (Lapidot-
Lefler & Barak, 2012). Lapidot-Lefler & Barak (2012) have further argued that anonymity may cause
social media users “to feel unaccountable for their negative actions, as they cannot behave identified as
the perpetrators of certain actions or behaviors”. This provokes toxic behaviour such as impulsive and
aggressive cyber-bullying and off-topic and off-color comments (Kietzmann et al., 2011). Seemingly, the
possibility to anonymity, whether in good or bad purpose, tempts people to express negative emotions in
social media.
Key complainers
All users are not equal in terms of their influence on diffusion of negative emotions online. Adapting
Russell’s circumplex model it seems quite self-evident that individuals who have emotionally negative
valence and positive arousal have different role than those who have negative valence and negative
arousal. Annoyed individual is probable more keen to ventilate in social media than disappointed one.
Users, who are biased to provide negative feedback in social media, can be labelled in many ways. Noble
et al. (2012), for example, have labelled them as “trolls”, “rager”, “misguided” and “unhappy customer”.
Although there are differences in behaviour between the labelled users, what they share is that they are
able to create non-linearly developing viral events that spread more widely and quickly than expected (cf.
Hemsley & Mason, 2013). Worth noting is that in recent years, many bloggers and twitterists have won a
superior audience size compared with traditional mediums (Sandes et al., 2013). It is expected that this
creates a fertile ground for emotional bursts.
Emergent result
Collective emotions result from the process where each individually continually decides with which other
actors it will engage, and what emotion it will share with them. Collective emotion is an emergent whole,
which display properties which cannot be traced back to individual contributions (Schweitzer & Garcia,
2010). This is what happened in the chain of events called “Arab Spring”. Arab Spring was a protest
movement which was initiated in Tunisia by a Facebook campaign run by the opposition “April 6 Youth
Movement” (Stepanova, 2011). The movement generated tens of thousands of positive responses to the
call to rally against government policies (Stepanova, 2011). During the movement social media carried
inspiring stories of protests. Mass forms of socio-political protest facilitated by social media networks
represent emergent behaviour as there is no possibility to pinpoint any specific event or act, which is
accountable for the rising local activities into regional, and in some extent even to global protest. The
power of “Arab Spring” rests on the movement’s ability to inspire disappointed and frustrated people into
collective action. Inflow of negative emotions leads to the emergence of patterns of themes which no
individual could have decided. Seemingly, things just happen without one particular reason. Collective
negative emotion, differs from individual negative emotion in terms of quantity and quality
The anatomy of the diffusion of negative emotion in social media is summarized in Figure 3.
Figure 3. The anatomy of collective negative emotion in social media.
5. A POSITIVE SIDE OF NEGATIVE EMOTION
From the organization’s perspective, negative emotional experiences are more dangerous than positive
one because they pose a threat to existence of organisation. Studies indicate that negative eWOM may
have very strong effects on organisations’ performance. Wangeheim (2005), Chevalier & Mayzlin (2006)
and Park & Lee (2009), among others, have identified that negative evaluations of products and services
have a stronger effect than positive ones. Negative eWOM affects negatively on brand image (Jansen et
al., 2009), consumers preferences (Khare et al., 2011) and purchase decisions (Fagerstrom & Ghinea,
2011). One possible explanation for this is that negative eWOM is more diagnostic than positive eWOM.
However, negative emotional experiences can also be valuable and useful for organisation. They can be
turned positive one. This is at least for two reasons. Firstly, as suggested before, for individual venting
negative emotions may act as catharsis helping people to feel calm and relaxed. For organisation this
offers an opportunity to engage emotionally with venting individuals. Many studies have found that
empathetic complaint management not only solve the problem but also strengthen customer relationship
(Estelami, 2000; Kirkby et al., 2001, Lee & Hu, 2004). A bit paradoxically, it has been found that
“customers rate service performance higher if a failure occurs and the contact personnel successfully
addresses the problem than if the service had been delivered correctly the first place (Hoffman & Bateson,
2001; Lee & Hu, 2004). Secondly, negative emotions may reveal unmet customer needs and preferences.
Von Hippel (2005), for example, has suggested that users of products and services themselves know the
best how the products and services actually meet their needs and how products and services should be
improved. Social media heralds of collaborative organisation in which employees, customers and other
stakeholders create spontaneously micro-scale innovation networks which can be exploited for solving
many resource problems (Morgan, 2012). Ignoring social network effects in the design process leads to a
substantially inferior product design (Gunnec & Raghavan, 2013) and to negative customer experience.
As social media also enables anonymity, which, in turn makes people more honest (e.g. Verhagen et al.,
2013), it is therefore reasonable to claim that social media is powerful tool for turning negative
experiences and emotions into positive ones.
6. CONCLUSIONS
This paper has proposed the anatomy of the diffusion of negative emotions in social media. The diffusion
of negative emotion is defined as a complex process. It is a process in which actors affect others and are
being affected by others. It is suggested that social media increase the odds that individually felt negative
emotions escalate into collective negative emotions. Individual negative emotions are inclined to
clusterize. As social media has removed time delays and physical distances, what has happened in local
level can become a global issue and other way round. Social media allows globallocal interplay in
venting negative emotions. Possibility to post negative information anonymously and the role of key
complainers enable non-linear dynamics. This may create emergent whole which cannot be traced back to
individual emotions. This paper does not contain any empirical data. Naturally, in order to validate the
anatomy of the diffusion of negative emotions, empirical research is needed.
This paper has not focused on any particular social media platforms. However, the findings of studies
which have compared different social media sites (Kietzmann et al., 2011; Hughes et al., 2012) implicate
that social media sites differ from each other based on their capacity to convey negative emotions. It can
be hypothesized, for example, that social media sites that allow anonymous posts differ on sentiment from
those sites which require identification. It has been proposed that Twitter offers greater user anonymity
than Facebook, which, in turn, may mean that Twitter provoke more “toxic” behavior (cf. Lapidot-Lefler
& Barak, 2012; Hughes et al., 2012). Furthermore, it can be supposed that mobile use of social media
potentially increase negative emotional bursts (cf. Kwon et al., 2013). This is because pocket carried
devices smart phones and tablets with wide range of applications enable almost real-time reaction, for
example, to bad customer service. This paper has not touched the economic consequences of negative
emotions, but on the basis of research done in negative eWOM, it can be, however, suggested that
organisation’s ability to detect negative sentiments related their products, services, brand images or
businesses becomes more and more importantly. This argument is in line with Rintamäki et al. (2007),
among others, who have identified that emotions play critical role in the competitive customer value
proposition.
The paper implicitly suggests that in order to handle negative emotions shared in social media, the
organization should aim at the ability to map the seeds of negative avalanches/groundswells as early as
possible. This is because the value of negative emotion is the function of time. One possible approach to
increase organisations’ ability to detect emotional weak signals is taking advantage of sentiment analysis
(Liu, 2010; Thelwall & Buckley, 2013). Sentiment analysis refers herein to computational study of
sentiments, affects and emotions expressed in social media texts. Sentiment analysis is based on the very
simple idea i.e. texts are subjective which may express some personal feeling, view, emotion, or belief.
Although, a completely automated solution is nowhere in sight (Lie, 2010), it is expected that sentiment
analysis provides useful tool organisations to improve their ability to detect symptoms of collective
negative emotions before they become an issue.
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... The following sections highlight some investigations focusing on associating emotions and social networks especially in Facebook and Twitter. Researchers have put in a lot of effort in realizing the dispersion of emotion through the content shared in social networks [8,9,10,11,12,13,14,15] Also, it is noted that most of the emotions are exchanged through Facebook and Twitter activities. ...
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... Similarly, Twitter has been serving as a good emotion diffuser through tweets [8,14,19,20,21]. According to these researchers, content, topic, messages, type of conversation, social ties, amount of network activity of individuals, participatory patterns, and language use act as emotion carriers in Twitter. ...
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Twitter is a popular microblogging service that is used to read and write millions of short messages on any topic within a 140-character limit. Popular or influential users tweet their status and are retweeted, mentioned, or replied to by their audience. Sentiment analysis of the tweets by popular users and their audience reveals whether the audience is favorable to popular users. We analyzed over 3,000,000 tweets mentioning or replying to the 13 most influential users to determine audience sentiment. Twitter messages reflect the landscape of sentiment toward its most popular users. We used the sentiment analysis technique as a valid popularity indicator or measure. First, we distinguished between the positive and negative audiences of popular users. Second, we found that the sentiments expressed in the tweets by popular users influenced the sentiment of their audience. Third, from the above two findings we developed a positive-negative measure for this influence. Finally, using a Granger causality analysis, we found that the time-series-based positive-negative sentiment change of the audience was related to the real-world sentiment landscape of popular users. We believe that the positive-negative influence measure between popular users and their audience provides new insights into the influence of a user and is related to the real world.
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Purpose ‐ The use of text-based communications such as instant messaging or social media such as Twitter has been growing significantly as the use of mobile devices increases. Not only do people share information via mobile communication, there are significant implications for advertising and marketing. Due to display limitations, however, the message senders use various conventions in addition to the text-based message to more clearly and richly express emotions. Since users use a range of expressions to convey these emotions, it would be very useful to verify the relationships between users' emotional expressions and receivers' perceptions of the expressions. The purpose of this paper is to propose an integrated model to examine the relationship between emotional expressions and the emotional intensity of the receivers. Design/methodology/approach ‐ The authors formulated a series of research hypotheses and tested them using empirical survey data. The research model used is based on regression analysis with dummy variables for statistical analyses. Findings ‐ First, emotional intensity had a closer relationship to user acceptance than was expected. Second, the use of exclamation marks and emotional messages are far less acceptable in negative messages. Third, the high formalisation group has a more positive emotional intensity in their basic expression. Originality/value ‐ The authors successfully determined that emotional expressions significantly affect the message receivers' emotional intensity and hence acceptance of the message.