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Negative emotions in social media as a managerial challenge

Authors:
Negative emotions in social media as a managerial challenge
Harri Jalonen
Turku University of Applied Sciences
Turku, Finland
harri.jalonen@turkuamk.fi
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
1. Introduction
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
media sites.
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 companys 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 populations 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
counterparts.
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, peoples 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.
4. Conclusions
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 organisations
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.
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... 9). Unlike a disgruntled customer with a legitimate complaint, a troll's intent is to deliberately damage a company (Jalonen, 2014). Negative comments can also be posted by cyberbullies who have previous knowledge or experience with the company. ...
... In his 2014 conference paper titled "Negative emotions in social media as a managerial challenge," Harri Jalonen posited that online emotional intelligence is an important characteristic required of a company participating in social media discussions (Jalonen, 2014). Jalonen (2014) said an organization develops online emotional intelligence through "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" (p. 7). ...
... Given the utilitarian nature of ATCOenergy's business as a utility, it can be argued that the informal metaphor, which capitalizes on the fact that February 2 is recognized as Groundhog Day, is unnecessary for a non-hedonic business and illustrates the danger of brands using an increasingly informal style on social media, as Barcelos et al. warn (Barcelos et al., 2018). Jalonen's (2014) invocation of online emotional intelligence, offer a deep perspective into motivations behind online conversations, emotion and negativity. Although only three studies were presented in the field of understanding online behaviour, the findings suggest the need to add several branches to the "Air Force Blog Assessment" decision tree, particularly on the "no" side. ...
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A negative comment on a corporate social media post can pierce like an arrow to the chest and puncture holes into an organization’s walls. A single negative voice in a sea of positive feedback can feel as though it is blaring from a giant bullhorn, striking fear into corporate community managers that an avalanche of negativity will overtake positivity like a contagious bandwagon. Why would a corporation consider telling its story in the online battlefield of social media and risk exposing its reputation to a cesspool of negativity? This paper will explore why negativity is an online barrier through research, industry advice and best practices – including from the researchers and experts who use the foregoing colourful idioms and metaphors to describe negative online comments. To answer the main question of why an organization would consider engaging on social media in the face of prolific negativity and hate speech, this paper will review the evolution of online emotions and the rise of negativity on social media. The paper will define negative online comments in the corporate context using research on trolls, cyberbullying and online personal attacks. Using the psychology of Pareto’s 80/20 rule and negativity bias, this paper will provide quantitative and qualitative perspectives on negativity to show why companies pay much more attention to negative comments than positive ones, and how analysis of negativity can help a company develop emotional intelligence. Examples will be presented from research and industry to understand and combat negativity and review research on user comments that classifies users to better understand their motivations. Using research on tone and voice in online conversation, this paper will share cautionary case studies that demonstrate how companies that are not self-aware can incite negative comments. Finally, this paper will review research on platform content moderation techniques to understand how social media platforms like Facebook manage negativity and will suggest similar solutions for corporations, including not only the online community’s ability but also our collective responsibility to moderate and overcome the online positivity deficit. Keywords: social media, community manager, online negativity, negativity bias, negative comments, online emotions, user categorization
... Consumer hatred against brands may result in passive (brand avoidance) and active (negative word of mouth and brand retaliation) harmful actions for the company and its brand (Grégoire et . With the advancements of internet technologies and social media, the customer's ability to express their negative brand emotions has increased (Jalonen, 2014). They can use anti-brand web sites to openly express their hate, which negatively affect purchase decision, brand identity, image and the company reputation (Kucuk, 2008). ...
... The Internet and social media enhance the customer's ability to express their negative emotions toward products, services and brands (Jalonen, 2014). Several websites enable customers to revise, rate and evaluate the products and the services provided by most companies (Delzen, 2014), such as Tripadvisor in tourism. ...
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Full-text available
Abstract Brand hate is considered as the most extreme and consecutive negative emotion toward brands which associated with various types of negative behavioral outcomes. Although the importance of the brand hate topic, the majority studies of customers' emotions towards brand were focused on positive emotions, while little researches focused on negative ones. Therefore, the purpose of this research is to explore and understand the brand hate and measure its drivers and outcomes among consumers in the Egyptian tourism sector. In this study, we develop and test a model that reshapes the interrelationship between the study variables. Structural Equation Model (SEM) is utilized to test the validity of the proposed model. The study is based on a quantitative methodology where 162 questionnaires were distributed. LISREL 8.80 program is used to test the theoretical model. The results reveal that experiential avoidance, identity avoidance and moral incompatibility are considered drivers of tourism products/services brand hate. Moreover, tourism products/services brand hate outcomes are identified as brand avoidance, negative word of mouth and brand revenge.
... Consumer hatred against brands may result in passive (brand avoidance) and active (negative word of mouth and brand retaliation) harmful actions for the company and its brand (Grégoire et . With the advancements of internet technologies and social media, the customer's ability to express their negative brand emotions has increased (Jalonen, 2014). They can use anti-brand web sites to openly express their hate, which negatively affect purchase decision, brand identity, image and the company reputation (Kucuk, 2008). ...
... The Internet and social media enhance the customer's ability to express their negative emotions toward products, services and brands (Jalonen, 2014). Several websites enable customers to revise, rate and evaluate the products and the services provided by most companies (Delzen, 2014), such as Tripadvisor in tourism. ...
Research
Full-text available
Brand hate is considered as the most extreme and consecutive negative emotion toward brands associated with various types of negative behavioral outcomes. Although the importance of the brand hate topic, the majority studies of customers' emotions towards the brand were focused on positive emotions, while little researches focused on negative ones. Therefore, the purpose of this research is to explore and understand brand hate and measure its drivers and outcomes among consumers in the Egyptian tourism sector. In this study, we develop and test a model that reshapes the interrelationship between the study variables. Structural Equation Model (SEM) is utilized to test the validity of the proposed model. The study is based on a quantitative methodology where 162 questionnaires were distributed. LISREL 8.80 program is used to test the theoretical model. The results reveal that experiential avoidance, identity avoidance, and moral incompatibility are considered drivers of tourism products/services brand hate. Moreover, tourism products/services brand hate outcomes are identified as brand avoidance, negative word of mouth and brand revenge.
... Consumer hatred against brands may result in passive (brand avoidance) and active (negative word of mouth and brand retaliation) harmful actions for the company and its brand (Grégoire et . With the advancements of internet technologies and social media, the customer's ability to express their negative brand emotions has increased (Jalonen, 2014). They can use anti-brand web sites to openly express their hate, which negatively affect purchase decision, brand identity, image and the company reputation (Kucuk, 2008). ...
... The Internet and social media enhance the customer's ability to express their negative emotions toward products, services and brands (Jalonen, 2014). Several websites enable customers to revise, rate and evaluate the products and the services provided by most companies (Delzen, 2014), such as Tripadvisor in tourism. ...
... Furthermore, they suggest that the timestamp would help to predict if the post is depression-indicative because one characteristic of depressed subjects is the nightly activity on the Internet due to insomnia. Other research work indicates that subjects with major depressive disorder show lower social activity, greater negative emotion, high self-attentional focus, increased relational and medicinal concerns, heightened expression of religious thoughts and belong to highly clustered close-knit networks [15]. Even though notable research has been published on the area of Text and Social Analytics, where several studies have attempted to predict or analyze depression [2,8,26] no one has attempted to build a dataset where a large chronological sequence of writings leading to that disorder is properly stored and analyzed [20]. ...
Chapter
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... Therefore, the identification and analysis substantiated the conceptual framework ( Figure 1) and the proposition of why and when an SMS can be regarded as a tourism marketing and branding "treat" (Eisenhardt, 1989). The findings inductively strengthened the framework and enriched the constructs by bringing new insights, which aligned with central findings in the literature on negative emotions expressed and shared on social media (Jalonen, 2014). ...
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Social media have emerged as a game changer for tourism by empowering consumers to collectively approve or oppose organizational behaviors. When consumers rise against organizations, social media storms (SMSs) can be an outcome. This research proposes a conceptual framework to help tourism organizations understand SMSs and to guide more effective decision making. Contextualized by a case study of the Copenhagen Zoo, it is shown how and why SMSs are an expression of negative consumer empowerment that brings challenges as well as opportunities. As demonstrated , an SMS can lead to a helix for value creation for the organization, consumers, and society. KEYWORDS consumer empowerment, Copenhagen Zoo, negative customer emotions, marketing management, social media storm (SMS), tourist attraction branding
... People love to share their emotions with others through writings [3]. The dominant emotions shared in online platform nowadays is via social media [8]. People express the highs and lows of their everyday life, ideas, opinions and events of interest with others. ...
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Emotions are the driving force for posting content on a social media platform. Although modeling and predicting in emotion with social media have been proposed, they often require post-investigation such as sentiment analysis. This often limits users to be aware of negative emotional states while publishing content on social media. In this project, we will propose an emotion detection technique by extracting the physiological responses of social media users from smartphone commodity sensors. We aim to provide design opportunities for social media platforms to raise emotional self-awareness of the users while using social media on the smartphone.
... Therefore, the identification and analysis substantiated the conceptual framework ( Figure 1) and the proposition of why and when an SMS can be regarded as a tourism marketing and branding "treat" (Eisenhardt, 1989). The findings inductively strengthened the framework and enriched the constructs by bringing new insights, which aligned with central findings in the literature on negative emotions expressed and shared on social media (Jalonen, 2014). ...
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Power dissemination between consumers and marketers is a topic of great interest, particularly under the prism of recent technological advancements. This paper conceptualizes and provides three case studies on how consumer empowerment and brand management are interrelated and attempts to shade a light on whether companies can utilize consumer empowerment in a constructive way for all involved parties. We propose that firms should not perceive consumer empowerment only as a potential threat, but also as an opportunity to communicate more effectively their brands' core values and to enhance their brands' awareness.
... Therefore, the identification and analysis substantiated the conceptual framework ( Figure 1) and the proposition of why and when an SMS can be regarded as a tourism marketing and branding "treat" (Eisenhardt, 1989). The findings inductively strengthened the framework and enriched the constructs by bringing new insights, which aligned with central findings in the literature on negative emotions expressed and shared on social media (Jalonen, 2014). ...
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This paper challenges the existing assumption that unwanted outcome of a social media shitstorm is caused by customers' negative outbursts toward the company. Rather it is the company's responsive actions toward negative social media communications that are requiring strategic considerations. A developed framework presents five aspects central to understanding the nature of shitstorms in order to provide a deeper understanding of the relationship between social media dynamics and customer empowerment through anger expression. The theoretical findings are empirically substantiated by three case studies and in-depth interviews with managers. The insights into companies' shitstorm responses and the strategic reasoning informing managerial decision-making suggest companies to rethink their strategic approaches to shitstorms. We contribute with a risk assessment model for companies to assess the potential impact of, and appropriate response to, customers' negative social media posts.
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Social media is believed to have played a central role in the mobilization of Algerian citizens to peaceful protest against their country’s corrupt regime. Since no one foresaw these protests (called ‘The Revolution of Smiles’ or ‘The Hirak Movement’), this research conducted social media analysis to elicit vital insights about both the intensity of sentiment and the influence of social media on this unexpected instigation of political protest. This work built a deep learning model and analysed the influence of content, sentiment and user features on information spread. The model used the learning capability of a long short-term memory network to predict ‘retweetability’. Experiments were conducted on two real-world datasets (Hirak and Brexit) collected from Twitter. User features were found to be a key element in the diffusion of information. The strongest feelings about event context actively influenced the spread of tweets. The Twitter emotion corpus was found to improve the predictive ability of the model developed in this study.
Book
In this thought-provoking work, Tony D. Sampson presents a contagion theory fit for the age of networks. Unlike memes and microbial contagions, Virality does not restrict itself to biological analogies and medical metaphors. It instead points toward a theory of contagious assemblages, events, and affects. For Sampson, contagion is not necessarily a positive or negative force of encounter; it is how society comes together and relates. Sampson argues that a biological knowledge of contagion has been universally distributed by way of the rhetoric of fear in the antivirus industry and other popular discourses surrounding network culture. This awareness is also detectable in concerns over too much connectivity, such as problems of global financial crisis and terrorism. Sampson’s “virality” is as established as that of the biological meme and microbe but is not understood through representational thinking expressed in metaphors and analogies. Rather, Sampson interprets contagion theory through the social relationalities first established in Gabriel Tarde’s microsociology and subsequently recognized in Gilles Deleuze’s ontological worldview. According to Sampson, the reliance on representational thinking to explain the social behavior of networking—including that engaged in by nonhumans such as computers—allows language to overcategorize and limit analysis by imposing identities, oppositions, and resemblances on contagious phenomena. It is the power of these categories that impinges on social and cultural domains. Assemblage theory, on the other hand, is all about relationality and encounter, helping us to understand the viral as a positively sociological event, building from the molecular outward, long before it becomes biological. https://www.upress.umn.edu/book-division/books/virality
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Individuals communicate and form relationships through Internet social networking websites such as Facebook and MySpace. We study risk taking, trust, and privacy concerns with regard to social networking websites among 205 college students using both reliable scales and behavior. Individuals with profiles on social networking websites have greater risk taking attitudes than those who do not; greater risk taking attitudes exist among men than women. Facebook has a greater sense of trust than MySpace. General privacy concerns and identity information disclosure concerns are of greater concern to women than men. Greater percentages of men than women display their phone numbers and home addresses on social networking websites. Social networking websites should inform potential users that risk taking and privacy concerns are potentially relevant and important concerns before individuals sign-up and create social networking websites.
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This study focused on exploring Internet abuse among teenagers and its relations to some Internet usage patterns and demographic characteristics in a digitalizing country, Turkey. It was designed as a cross–sectional research on three types of school that differ in their academic performances. The data were collected from 1380 high school students through a paper–based questionnaire. The results identified a small portion of students as Internet abusers experiencing severe problems and one fourth as possible abusers experiencing occasional problems in their lives. Excessive use, tolerance, preoccupation with the Internet, and using the Internet to escape from negative feelings were the most frequently reported symptoms of disturbed patterns of online behaviors. One–way between–groups ANOVA tests revealed that Internet abuse differed significantly based on gender and perceived academic achievement with small effect sizes, and frequency of Internet use, dominant place of Internet use and dominant purpose for Internet use with medium and large effect sizes. On the contrary, no significant differences were found based on perceived socio–economic status and the type of school attended.
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Service failure is unavoidable. However, depending on the type of loyalty, customers react differently to critical incidents causing dissatisfaction, e.g. truly loyal customers are less inclined to end the relationship with their provider. Intending to stay, they will instead complain to the company. The type of customer loyalty also influences the channel choice for com-municating dissatisfaction. As online complaints require more trust in the company, e-communication is more likely to be chosen by truly loyal customers. This paper provides a conceptual framework demonstrating the effects of customer loy-alty on complaint response patterns and channel choice using the example of the complaint response "voice company".
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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.
Article
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.