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Applying “Negativity Bias” to Twitter: Negative News on Twitter, Emotions, and Political Learning

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This study examined effects of negative news on Twitter users’ emotional, cognitive and behavioral responses. Four hundred twenty subjects participated in an online experiment and read 10 news stories, modified as Twitter newsfeed. The results show that news negativity had a significant effect on anger and disgust. A significant link was found between exposure to negative news and information seeking. The impact of news negativity on emotions and political learning was moderated by age. Findings also reveal that experiencing negative emotions as a result of exposure to negative news on Twitter is not necessarily at odds with achieving political learning.
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Journal of Information Technology & Politics
ISSN: 1933-1681 (Print) 1933-169X (Online) Journal homepage: http://www.tandfonline.com/loi/witp20
Applying “Negativity Bias” to Twitter: Negative
News on Twitter, Emotions, and Political Learning
Chang Sup Park
To cite this article: Chang Sup Park (2015) Applying “Negativity Bias” to Twitter: Negative News
on Twitter, Emotions, and Political Learning, Journal of Information Technology & Politics, 12:4,
342-359, DOI: 10.1080/19331681.2015.1100225
To link to this article: http://dx.doi.org/10.1080/19331681.2015.1100225
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Journal of Information Technology & Politics, 12:342–359, 2015
Copyright © Taylor & Francis Group, LLC
ISSN: 1933-1681 print/1933-169X online
DOI: 10.1080/19331681.2015.1100225
Applying “Negativity Bias” to Twitter: Negative News on
Twitter, Emotions, and Political Learning
Chang Sup Park
ABSTRACT. This study examined the effects of negative news on Twitter users’ emotional, cognitive,
and behavioral responses. Four hundred twenty subjects participated in an online experiment and read
10 news stories, modified as Twitter newsfeed. The results show that news negativity had a significant
effect on anger and disgust. A significant link was found between exposure to negative news and infor-
mation seeking. The impact of news negativity on emotions and political learning was moderated by
age. Findings also reveal that experiencing negative emotions as a result of exposure to negative news
on Twitter is not necessarily at odds with achieving political learning.
KEYWORDS. Emotions, negative news, negativity bias, political learning, Twitter
Social media increasingly draw attention as
a rapidly growing channel for news consump-
tion. News consumption via social media has
increased by over 50% since 2009 in the
United States (Weeks & Holbert, 2013). Social
media have also become one of the dominant
channels for citizens to obtain political news
(Thelwall, Wilkinson, & Uppal, 2009). Despite
rapid growth as an important vehicle for elec-
tion news, social media are frequently blamed as
a hotbed of “bad news.” During the 2012 U.S.
presidential election in South Korea, Twitter
was a battleground where “rumor-mongering,”
“deviant,” or “negative” news stories about
candidates were delivered to voters (Lee &
Hong, 2012). The Pew Research Center (2012)
reported in a study of the social media cam-
paign during the 2012 election that the tone
Chang Sup Park is an assistant professor of mass communications at Bloomsburg University of
Pennsylvania. His research interests are in social/mobile media, civic engagement, political participation,
and digital journalism.
Address correspondence to: Chang Sup Park, Department of Mass Communications, Bloomsburg
University of Pennsylvania, 400 E. Second Street, Bloomsburg, PA 17815 (E-mail: cpark@bloomu.edu).
Color versions of one or more of the figures in the article can be found online at http://www.tandfonline.
com/WITP.
of information in social media was consistently
more negative than that observed in traditional
news outlets. It noted that Twitter was by far
the most negative among various social media.
In the analysis of more than 1.2 million tweets
in English, French, and German collected in
May 2014, 39% of the assertions on Twitter in
English and French were negative toward the
EU elections, compared with 31% (English) and
33% (French) that were positive (Pew Research
Center, 2015).
The inundation of “bad” news into social
media raises an important question regarding
the role of social media in the political process.
Does negative news result in political cynicism
or bring about a stimulation effect? By and
large, negative news influences recipients’ atti-
tudes, feelings, and behavior (Kleinnijenhuis,
342
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Park 343
van Hoof, & Oegema, 2006). For example,
negativity in political campaigning tends to
disenfranchise voters and could cause low
voter turnout and less involvement in elections
(Ansolabehere & Iyengar, 1995). Messages of
social media focusing on negativity could be
more worrisome, considering that social media
are becoming increasingly a vital tool to acquire
election information (Park, Barnett, & Chung,
2011). The impacts of negative news on human
perception and behavior have been frequently
documented in traditional media contexts such
as television news (Izard, 1993; Sweeny &
Shepperd, 2009). But knowledge about the
impact of negative news in social media is lim-
ited.
Drawing on the above reasoning, this study
aims to examine two things. First, it probes
whether and how the negative news on social
media influences users’ feelings, recall, and
information seeking, mainly based on the the-
ory of negativity bias, which posits that negative
information is perceived as more salient and
efficacious than positive information (Rozin &
Royzman, 2001). To this end, the present study
chooses to study Twitter because of its popular-
ity along with its unique features as a powerful
tool for news acquisition and exchange. Twitter
is an ideal platform through which news is prop-
agated, shared, and discussed among diverse
users (Boyd, Golder, & Lotan, 2010). In partic-
ular, Twitter has become a legitimate and fre-
quently used communication channel for polit-
ical parties, politicians, and citizens (Tumasjan,
Sprenger, Sandner, & Welpe, 2011).
Another purpose of this study is to explore
the moderating role of age between news neg-
ativity and political reaction. Research shows
that young people tend to be more responsive
to news influence emotionally, cognitively, and
behaviorally than older adults (Bachmann et
al., 2010; Jansen et al., 2008; Orgeta, 2009).
This research extends the discussion about the
impact of age to the context of social media.
To date, most studies have focused on how
social media use for news has an impact either
on the general public (e.g., Gil de Zúñiga,
Jung, & Valenzuela, 2012; Kwak et al., 2010),
or on young adults only (e.g., Baumgartner
& Morris, 2010). Attempts to differentiate the
impact of news consumption via social media
between young and old adults have been rare.
Considering that the chances of young people
being exposed to negative political news through
social media is becoming higher because of their
increasing dependence on social media, it is
important to examine what different influences
negative news flow on social media will exercise
for people varying in age.
To those ends, the present study conducted
an online experiment of 420 voters during the
2014 local elections in South Korea. The elec-
tion campaign, being an unprecedented negative
campaign as compared to other Korean cam-
paigns (Park, 2014), provides a good case to
investigate the role of negative news on Twitter
in the political process. The choice of South
Korea for this study can be further justified by
the fact that Twitter is robustly used to distribute
information, trigger discussion, and mobilize
collective actions in this nation (Hsu, Park, &
Park, 2013), reshaping the nation’s political cul-
ture.1
LITERATURE REVIEW
Twitter and Political News
Since its launch in 2006, Twitter has shown
an exponential increase in the number of users,
becoming the third largest social networking
site behind Facebook and YouTube (Parmelee
& Bichard, 2012). By the end of 2014, Twitter
had more than 284 million users worldwide
(Statistica.com, 2015). Twitter can be character-
ized by its simple and easy features. It limits
uploaded messages (tweets) to 140 characters.
Twitter is accessible anywhere and anytime,
making it possible for people to share public
and private information with a wider audience
(Swigger, 2013). Twitter is also a communi-
cation tool that can carry “rich” information.
It can include links to other Web sites providing
additional information and contain hashtags that
provide topical context (Parmelee & Bichard,
2012). In addition, the retweet function makes
Twitter powerful by allowing users to forward
messages to other users. In short, Twitter, by
motivating users to publicize themselvesin ways
that have never been possible before, is changing
Downloaded by [Bloomsburg University], [Chang Sup Park] at 06:12 16 February 2016
344 JOURNAL OF INFORMATION TECHNOLOGY & POLITICS
the nature of social communication (Swigger,
2013).
This study attends to the fact that Twitter
is increasingly perceived and used as a news
outlet partly because of the aforementioned fea-
tures (Kwak, Campbell, Choi, & Bae, 2011).
Many studies document that Twitter is widely
used as a means of news acquisition and sharing
(Honey & Herring, 2009; Java, Song, Finin, &
Tseng, 2007). According to Hansen, Arvidsson,
Nielsen, Colleoni, and Etter (2011), 23% of
all tweets can be regarded as news. In partic-
ular, Twitter is extensively used for the dis-
semination of political news stories across the
world such as Iran (Gaffney, 2010), Germany
(Tumasjan et al., 2011), Sweden (Larsson &
Moe, 2012), and the United States (Wattal,
Schuff, Mandviwalla, & Williams, 2010). Many
politicians and traditional media outlets often
use Twitter to directly meet citizens (Spierings
& Jacobs, 2014). Indeed, scrolling the time line
of Twitter, people scan quickly a variety of
news stories about elections. This explains why
Twitter is particularly popular during elections.
During the 2012 presidential election in South
Korea, Twitter was one of the primary vehi-
cles for news distribution (Lee & Hong, 2012).
However, negative information constitutes a sur-
prisingly large portion of tweets. In an analysis
of 2,457 stories in 49 mainstream news sources,
along with millions of tweets in the United
States, Pew Research Center (2012) found that
every week on Twitter resembled the worst
week for each candidate in the mainstream
media.
Negativity Bias
Then how does negative news on Twitter
influence citizens’ political attitudes and behav-
iors? To answer this question, the current
study draws on the theory of negativity bias.
Negativity bias refers to a phenomenon whereby
humans tend to put more emphasis on negative
information than on positive information in their
feelings, judgments, and information-processing
tasks (Lang, Park, Sanders-Jackson, Wilson,
& Wang, 2007; Rozin & Royzman, 2001).
Research has consistently shown that negative
news elicits more attention than does good news
(Grabe & Kamhawi, 2006; Zillmann, Chen,
Knobloch, & Callison, 2004). In other words,
negative information tends to elicit stronger and
quicker emotional, cognitive, and behavioral
responses than neutral or positive information
(Baumeister, Bratslavsky, Finkenauer, & Vohs,
2001;Taylor,1991).
Several explanations have been proposed
to explain negativity bias. One of them con-
cerns perceptual salience (see Skowronski &
Carlston, 1989 for a review); negative informa-
tion attracts more attention from people than
positive information and, as a result, it is more
likely to be selected (Fiske, 1980; Steiner, 1979).
In Donsbach’s (1991) study on readers’ selec-
tion of articles about politicians in German
newspapers, negative headlines were selected
more frequently than positive headlines because
of perceptual salience.
Another explanation concerns human evolu-
tion. Over the course of biological and cultural
evolution, the human brain has become adapted
to the task of noting information that can secure
survival and reproduction, in particular, infor-
mation about potentially threatening situations
(Davis & McLeod, 2003). Shoemaker (1996)
argued that because the human brain is “hard
wired” by biological forces, people attend to
deviant events and occurrences. Scores of stud-
ies have confirmed Shoemaker’s claim (Canli,
Desmond, Zhao, & Gabrieli, 2002; Grabe, Lang,
& Zhao, 2003;Zald,2003).
Negativity bias holds across a wide range
of domains. Research in social psychology and
political communication has consistently found
that negative information has a stronger impact
on how people process information than positive
information (Ito, Larsen, Smith, & Cacioppo,
1998; Lau & Pomper, 2004). However, there
have been few attempts to apply the negativ-
ity bias theory to understanding of citizens’
political action via social media, although it is
expected that people are much more likely to
recognize and to be influenced by the negative
information provided through social media. This
study tests negativity bias in the Twittersphere
by looking at diverse impacts of negative news
disseminated through Twitter.
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Park 345
Negative News and Emotional Reaction
In testing negativity bias, the current study
first examines how negative news on Twitter
relates to discrete emotions. Emotions are gen-
erally defined as internal mental states that
are caused by an evaluation of events, people,
or objects (Ortony, Clore, & Collins, 1988).
Emotion is a vital component in human com-
munication (Izard, 1977;Thelwalletal.,2009).
There is evidence that at least five different
emotions (fear, disgust, anger, happiness, sad-
ness) exist, with each emotion activating dif-
ferent combinations of brain regions (Murphy,
Nimmo-Smith, & Lawrence, 2003). This study
focuses on three negative emotions: anger, fear,
and disgust.
The choice of the three negative emotions was
made mainly for three reasons. First, they are
all considered high-arousal negative emotions
(Newhagen, 1998; Valentino, Hutchings, Banks,
&Davis,2008), which are contrasted with
low-arousal negative emotions such as sadness.
By focusing on the three negative emotions,
this study expects to find a clear connection
between negative news and negative emotions.
Second, this study aims to develop the negativity
bias theory by investigating how emotional reac-
tions triggered by negative news on Twitter are
associated with subsequent information-seeking
and -processing behavior. Prior research has
shown that highly negative emotions have dis-
tinct impacts on behavioral tendencies (Huddy,
Feldman, & Cassese, 2007; Isbell, Ottati, &
Burns, 2006; Marcus, Sullivan, Theiss-Morse, &
Stevens, 2005).
Last, the impact of negative news on anger,
fear, and disgust has been widely documented
by numerous studies (Lang, Newhagen, &
Reeves, 1996;Langetal.,1996; Miller &
Leshner, 2007; Newhagen, 1998; Newhagen &
Reeves, 1992). Anger is generally elicited when
one is compelled to do something against one’s
wishes. Anger is believed to mobilize and to
sustain high levels of energy to defend oneself
(Averill, 1983; Izard, 1993),andtomakeone-
self more physically and cognitively acute in the
face of threats (Henry, 1986; Newhagen, 1998).
For instance, when people read a story about an
abrupt tax increase, they may reveal a high level
of anger. Fear is generally incited when a situa-
tion is perceived as threatening to one’s physical
or psychological self (Frijda, 1986; Scherer,
1984). Fear involves uncertainty about one’s
ability to withstand or to handle a given threat
(Ohman, Hamm, & Hugdahl, 2000). Newhagen
and Lewenstein (1992) found that exposure to
television news saturated with images of damage
and fire corresponded to higher levels of fear.
Disgust is aroused by events or objects that are
organically or psychologically spoiled (Rozin,
Haidt, & McCauley, 1993). It can be expressed
as the form of nausea, repulsion, or avoid-
ance (Izard, 1977; Lazarus, 1991). Disgust is a
response to passive or latent danger, although it
is less compelling than fear or anger (Newhagen,
1998). Therefore, disgust could be another emo-
tion that is invoked by negative news. In a nut-
shell, negative content tends to elicit emotions
of anger, fear, and disgust.
Are then emotional reactions to negative news
online similar to those found in offline media
channels? According to Derks, Fischer, and
Bos (2008), explicit emotional communication
is more frequently found in computer-mediated
communication than in face-to-face communi-
cation. Chmiel et al. (2011) found that negative
posts on an online discussion forum raise the
average level of negative emotions in a discus-
sion thread. Drawing on the literature, this study
predicts:
H1: Highly negative news stories on Twitter
will arouse stronger anger, fear, and disgust than
weakly negative news stories on Twitter.
Negative News and Political Learning
Research found that negative news can lead
to higher interest in, deeper processing of, and
better recall of the news to which the audiences
are exposed (David, 1996). In other words, nega-
tive news stories exercise a significant influence
on the cognition of human beings. According
to Lang, Newhagen, and Reeves (1996), nega-
tive news stories increase the capacity required
to process the message, the ability to retrieve
the story, and the recognition of information.
Straughan (1989) found that news items contain-
ing “conflicts” scored higher in reader interest
than items that did not contain conflict.
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346 JOURNAL OF INFORMATION TECHNOLOGY & POLITICS
According to the distinctiveness hypothesis,
deviant stories draw more attention, resulting
in deeper processing and better recall (David,
1996). Based on the theory, several studies
found that novel or distinctive stimuli are
remembered better than less distinct stimuli
(Hunt, 1995). The limited capacity model of
mediated message processing (Lang, 2000)also
suggests that negative pictures and news sto-
ries are more likely to elicit emotional arousal
and increase salience and availability in mem-
ory. The direct effect of negativity on memory
has been found in several experimental studies
(Bless, Hamilton, & Mackie, 1992; Robinson-
Riegler & Winton, 1996). Based on the litera-
ture, this study poses:
H2: Highly negative news stories on
Twitter will be better recalled than
weakly negative news stories on
Twitter.
People tend to stay vigilant for their envi-
ronment, in order to watch out what is taking
place in the world around them. This tendency
is often referred to as “surveillance” motivation.
According to Shoemaker (1996), the motive to
consume negative news can be closely associ-
ated with a human tendency of surveying the
environment for things that are unusual or may
cause potential threats. Surveillance is one of
the key motivations that people feel after expo-
sure to negative news. To resolve the uncertainty
caused by negative news and to control the situ-
ation related to the negative news, people tend
to seek additional information (Atkin, 1973;
Eggly et al., 2006). In other words, additional
information-seeking behavior after exposure to
negative news can be considered an appropri-
ate strategy for coping with the uncertainty and
threats caused by news negativity.
H3: Highly negative news stories on
Twitter will trigger more active
information-seeking behavior than
weakly negative news stories on
Twitter.
Interaction of Age and News Negativity
This study also examines the interaction of
age and news negativity. In general, young
adults tend to disengage themselves from
politics more than their older counterparts
(Bauerlein, 2008; Mindich, 2005; Wattenberg,
2007). Young people are less likely to partici-
pate in political activities, such as voting, money
donation, volunteering, or attending political
rallies than older people. In South Korea, the
turnout of young voters (19–29) in presidential
elections has been consistently lowest among
all age groups since the country adopted the
direct election for the president in 1987 (Kim &
Hamilton, 2006).
How then does news consumption via social
media influence young and old people’s polit-
ical attitudes? Are young adults more vulner-
able to negative news on Twitter than older
adults? Given that there has been little empirical
research, it is not easy to answer the question.
Two considerations can be brought up. First,
the media consumption habit of today’s young
people differs from that of older people. Young
people are less likely than their older counter-
parts to read newspapers or to tune in to news
on television or radio (Baumgartner & Morris,
2010). However, young people in their 20s or
30s are obviously the most frequent users of the
Internet. Social media, especially, are a prime
communication tool for young adults. Most of
them have social media accounts and make
heavy use of them (Pew Research Center, 2008,
2015). Also, it seems that the frequency of social
media use leads to different responses to neg-
ative news on Twitter between young and old
age groups. It is plausible that youths are more
responsive to negative messages via Twitter than
older adults.
Second, in general younger people are more
susceptible to stimuli than older people. They
tend to lose their temper even at a small
offense (Pulkkinen, 1996). According to Orgeta
(2009), younger adults find it harder to reg-
ulate emotion than older people. Older adults
tend to be good at controlling impulsive emo-
tions than younger adults, maintaining emo-
tional stability (Carstensen et al., 2011). In other
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Park 347
words, age is correlated with emotion con-
trol. Thus, it is expected that younger people
will show a higher level of negative emotions
than older people after exposure to negative
news on Twitter. In terms of recall, older peo-
ple have more trouble remembering negative
information than younger ones (Jansen et al.,
2008). Regarding political behavior, Rahn and
Hirshorn (1999) found that exposure to nega-
tive advertising altered young people’s political
attitudes. To date, few studies have compared
the difference in the impact of negative news
on political behavior between young and old
adults. Considering that there has been little
research about the moderating role of age in the
social media context, the present study poses a
research question:
RQ1: How does age influence the rela-
tionship between exposure to neg-
ative news on Twitter and discrete
emotions, recall, and information
seeking?
Relationship between Emotion and
Political Learning
The conventional wisdom about the role of
emotion in politics is that negative emotions
tend to degrade the quality and quantity of pub-
lic information seeking, deliberation, and politi-
cal knowledge. Modern political philosophy has
continuously denigrated the role of emotion in
democratic systems (see Corcoran, 2004 for a
review). However, evidence from social psy-
chology refutes such a claim. Recent research
has led to a number of insights about the role
of emotion in triggering political interest, atten-
tion, learning, and behavior (Huddy et al., 2007;
Isbell et al., 2006). For instance, Forgas (2006)
claims that emotions “influence what we notice,
what we learn, what we remember, and ulti-
mately the kinds of judgments and decisions
we make” (p. 273). Research also shows that
emotions often have carry-over effects on judg-
ment and behavior (Ellsworth & Scherer, 2003),
eliciting cognitive responses such as attention
(Bayer, Sommer, & Schacht, 2012; Kissler,
Herbert, Peyk, & Junghofer, 2007), and an
increased level of cognitive involvement may
in turn lead to a higher likelihood of behav-
ioral response (Honey & Herring, 2009; Peters,
Kashima, & Clark, 2009).
In what ways then do discrete emotions
relate to political learning and behavior? An
approach–avoidance claim may be useful in
untangling the mechanism (see Buck, 1984).
It details how human responses serve as an adap-
tive mechanism in a threatening environment.
The basis for the claim rests on an explanation
that emotions, as a response system, adjust and
tune the human organism to rapid and possibly
threatening changes in the environment (Frijda,
1988). When a novel object enters the environ-
ment, the behavioral decision is simply whether
to approach or avoid it (Izard & Buechler, 1980).
Each of the three primary negative
emotions—anger, fear, and disgust—can
be described in terms of unique responses
to threats in the environment and approach–
avoidance strategies. Anger arises when
undesirable outcomes are predictable or have
occurred repeatedly in the past. Consequently,
individuals experiencing anger tend to feel
certain about subsequent situations (Lerner &
Keltner, 2001). As a result, anger leads to hostile
approach behaviors such as lashing out or ret-
ribution (Newhagen, 1998; Roseman, Wiest, &
Swartz, 1994). Anger might then cut off further
attempts to gather and integrate new informa-
tion, depressing information-seeking behavior
(Valentino et al., 2008). Furthermore, angry
people are more likely to engage in heuristic
processing that requires little direct thought
and relies on rules of thumb (Bond, Bettman,
& Luce, 2008). For example, angry individ-
uals have been shown to make shortsighted
inferences, base judgments on stereotypes,
and attend insufficiently to argument quality
(Lerner, Goldberg, & Tetlock, 1998; Tiedens &
Linton, 2001). In other words, anger prompts
reliance on superficial cues rather than careful
deliberation, which may inhibit political learn-
ing and the willingness to gather additional
information about the issue in question.
H4: Anger caused by negative news on
Twitter will be negatively related to
information seeking.
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348 JOURNAL OF INFORMATION TECHNOLOGY & POLITICS
H5: Anger caused by negative news on
Twitter will be negatively related to
recall.
Fear is evoked by the presence of unpre-
dictable threats (Lazarus, 1991). Fear is more
often triggered when an individual is not certain
about stimuli (Lerner & Keltner, 2001; Tiedens
& Linton, 2001). Fear motivates a person to
avoid potential harm arising from ambiguous
threats and to pay attention to current cir-
cumstances and threatening stimuli (Lazarus,
1991; Lazarus & Lazarus, 1994; ). The over-
all response of fear is to prepare for a sudden,
intense explosion of muscular effort directed
toward flight (Henry, 1986). While anger trig-
gers the use of cognitive heuristics, fear tends
to result in more systematic information pro-
cessing (Bohner & Weinerth, 2001; Tiedens &
Linton, 2001). As a result, fear is expected to
boost political learning and information seeking
(Valentino et al., 2008).
H6: Fear caused by negative news on
Twitter will be positively related to
information seeking.
H7: Fear caused by negative news on
Twitter will be positively related to
recall.
Disgust, on the other hand, does not con-
tain the urgency of fear or anger. The avoid-
ance response associated with it is more an
act of rejection than it is of flight. It is physi-
cally manifested by a pushing away, or sensory
shutdown (Plutchik, 1980). Therefore, the cog-
nitive or behavioral outcome caused by disgust
is expected to be smaller compared with the
outcome caused by anger or fear (Figure 1).
RQ2: In what ways is disgust triggered
by negative news on Twitter asso-
ciated with recall and information
seeking?
FIGURE 1. Theorized model.
The Political System and Twitter Use in
South Korea
The political system of South Korea is based
on a republic form of government with the pres-
ident as chief of the state and the prime minister
as head of the executive branch. Powers of the
government are shared among the executive,
legislative, and judiciary branches, but the pres-
ident has the most dominant power like in the
United States. The legislative branch consists of
the unicameral National Assembly, the members
of which are elected for a four-year term. There
are 299 members in the National Assembly;
243 members are in single-seat constituencies
and 56 are elected by proportional representa-
tion. As of August 2015, the ruling Saenuri Party
occupies 160 seats of the Assembly and the main
opposing party, The New Politics Alliance for
Democracy, has 130 seats.
Twitter is the most dominant social media in
Korean politics. In terms of users receiving the
highest number of replies, half or a third of the
top 25 users are South Koreans (Kong, Park,
&Han,2009). According to a recent survey
by Global Web Index, a global market research
firm, as of the third quarter of 2013, 56% of
Korean Internet users had Twitter accounts, and
22% used Twitter in the past month.2Twitter has
been frequently used to disseminate informa-
tion, spark up debates, and organize collective
actions in South Korea (Hsu et al., 2013). After
first rising to prominence as a tool for politi-
cal engagement during the 2010 local elections
in South Korea, Twitter has played a pivotal
Downloaded by [Bloomsburg University], [Chang Sup Park] at 06:12 16 February 2016
Park 349
role in shaping the country’s political landscape.
In today’s Korean politics, Twitter is widely
used by social and political groups to articulate
information and mobilize supporters.
Previous studies have examined the role of
Twitter in political discourse mainly in Western
contexts or in the context of political upheavals
in the Middle East (Tufekci & Wilson, 2012;
Howard & Hussain, 2013). In this regard, under-
standing the ways in which Twitter use influ-
ences political attitudes, learning, and behavior
of Koreans can provide valuable data for a
global comparison.
METHODS
This study employed a 2 (news negativity—
high and low) ×3 (age—young, middle-aged,
and old) factorial design.
Stimuli
At the first stage, 40 news articles from the
top four nationwide newspapers of South Korea
(Chosun, Joongang, Donga,andHankyoreh)
were selected during the 2014 local elections
(May 4–June 3). Articles were chosen so that
they contained a mix of high and low neg-
ative topics about the campaign and candi-
dates. To prevent any political bias, partisan
indicators were removed. Newspaper names,
reporter names, and publication dates were also
removed. A short version (within 140 charac-
ters) for each article was produced to fit the
Twitter format. Each revised article was placed
on a separate PowerPoint slide.
At the second stage, a manipulation check
was conducted with 20 voters. They were asked
to view the PowerPoint file that contained the
40 revised Twitter-version articles and to rate
each article for negativity. Drawing on the
study of Larsson, Lindstedt, Löwgren, Reimer,
and Topgaard (2008), this study asked respon-
dents, “How negative do you feel about the
news?” The responses were coded on a 5-point
scale ranging from not at all to extremely.
Based on the average score each news arti-
cle obtained, five “highly negative” and five
“weakly negative” stories were chosen (Table 1).
A paired-samples ttest indicated that the
mean for the top five highly negative stories
(M=4.18, SD =1.87) was significantly greater
than the mean for the top five weakly negative
stories (M=2.61, SD =1.60).
Participants
There is no general consensus about the
breakdown of age. Petry (2002) suggested the
following classification: young adults (18–35),
middle-aged adults (36–55), and older adults
(over 55). Kleemans et al.’s (2012) categoriza-
tion is a little different: young adults (18–29),
middle-aged adults (30–50), and older adults
(over 51). In South Korea, the minimum age
for voting is 19, and people from 30 to 45 are
usually called middle-aged. Thus, this study
uses the following age brackets: “young adults”
(19–29), “middle-aged adults” (30–45), and
“old adults” (over 46).
Across the three age groups, a total of
420 voters (207 female and 213 male) were
recruited who identified themselves as Twitter
users. Sixty subjects were assigned to each
group. The average age was 35.7 (young adults:
M=23.56, SD =2.04; middle-aged adults:
M=37.91, SD =4.61; old adults: M=53.89,
SD =5.48). Half of the subjects in each age
group were exposed to the low negativity con-
dition and the other half to the high negativity
condition.
Procedure
A Web page was created to mimic the struc-
ture of the Twitter newsfeed. The 10 cho-
sen articles were placed within the newsfeed.
Each article was placed on a separate page.
Then participants were asked to read each news
article placed on a fabricated Twitter page.
After reading each story, subjects rated their
level of anger, fear, disgust (anger: M=2.73,
SD =.93; fear: M=1.75, SD =1.06; dis-
gust: M=2.14, SD =.98) and likelihood to
seek additional information related to the news
(M=2.93, SD =1.06) on a 5-point scale. Then,
a five-minute entertainment video was shown
to the participants, to prevent possible impacts
of short-term memory on a subsequent recall
test. After watching the video, subjects were
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350 JOURNAL OF INFORMATION TECHNOLOGY & POLITICS
TABLE 1. Means and Standard Deviations of Top 5 Highly Negative Stories and Top 5 Weakly
Negative Stories
Five highly negative stories (modified to fit into Twitter newsfeed) MSD
1. 13% of the candidates did not fulfill compulsory military service, and 40%
were found to be ex-convicts.
4.58 1.75
2. Moon publicly labeled Koh as “knowing nothing about education.” 4.43 1.89
3. Vicious rumors about the candidate Cho in Suncheon were spread widely 5
days before the election.
4.17 2.05
4. Several supporters poured abusive language to the candidate publicly and
the police undertook an investigation for that.
4.02 1.75
5. A total of 337 candidates or their aides were involved in illegal campaigning
during the election, the police said.
3.94 1.90
Five weakly negative stories
1. The Election Management Committee overlooked several illegal campaign
activities by the ruling party.
2.39 1.58
2. The televised debate for the Incheon mayoral post resulted in scathing
criticisms against one another.
2.49 1.53
3. Chung blamed Park, raising suspicion that Park intentionally kept his wife
from appearing in public for some reason.
2.63 1.54
4. Ruling Saenuri Party blamed the opposition parties of forming alliances for
the upcoming elections, calling such moves “forbidden fruit.”
2.74 1.65
5. Chung accused Park of not providing enough city funds for safety and
ignoring the Seoul subway’s air quality problem.
2.78 1.72
asked to answer five questions about the stories.
Responses to each recall question were coded as
0 (incorrect) or 1 (correct) and were averaged to
create an index (M=.62, SD =.84).
RESULTS
A series of two-way ANOVA were run to
evaluate the effects of news negativity and age
on discrete emotions, recall, and information
seeking. Initially, main effects and their post-hoc
results were identified. If an interaction effect
was identified, additional contrast analyses were
conducted.
Impacts of News Negativity and Age on
Emotions
A main effect for news negativity on anger
was found (F(1, 414) =149.34, p<.001, par-
tial η2=.27), indicating that highly negative
news on Twitter causes more anger than weakly
negative news. The effect size was large (Cohen,
1988).3A large main effect for age on anger was
also found (F(2, 414) =15.02, p<.001, par-
tial η2=.07). A Tukey HSD test revealed that
FIGURE 2. The moderating role of age
between news negativity and anger.
young adults (M=2.66) felt more anger as a
result of exposure to negative news than middle-
aged (M=2.35) and old adults (M=2.12).
There was also a significant interaction between
news negativity and age, F(2, 414) =24.39,
p<.001, partial η2=.11 (Figure 2).
Contrast analyses with Bonferroni adjust-
ments were carried out to compare the means
of the three age groups. Highly negative
news stories had a bigger effect on old
adults (Mhighnegative=2.82, Mlownegative=
1.42, Mdiff =1.40) than on young adults
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Park 351
(Mhighnegative=2.90, Mlownegative=2.42,
Mdiff =.48). The difference reached sig-
nificance, F(1, 414) =12.72, p<.001.
Highly negative news stories had a stronger
influence on old adults than on middle-aged
adults (Mhighnegative=2.69, Mlownegative=2.01,
Mdiff =.68). Again, the difference in impact
was significant, F(1, 414) =9.38, p=.009.
Results revealed that only age had a signif-
icant main effect on fear (F(2, 414) =7.14,
p=.001, partialη2=.03) with a medium
effect size, while news negativity did not.
A Tukey HSD test revealed that young
adults (M=1.85) and middle-aged adults
(M=1.82) felt more fearful than old adults
(M=1.55). No significant difference was found
between young and middle-aged adults. The
analyses found a significant interaction between
news negativity and age, F(2, 414) =8.13,
p<.001, partial η2=.04 (Figure 3 and
Figure 4).
FIGURE 3. The moderating role of age
between news negativity and fear.
FIGURE 4. The moderating role of age
between news negativity and disgust.
Contrast analyses found that highly neg-
ative news stories had a stronger effect on
young adults (Mhighnegative=2.04, Mlownegative=
1.66, Mdiff =.38) than on middle-aged
adults (Mhighnegative=1.74, Mlownegative=1.90,
Mdiff =−.16, F(1, 414) =85.35, p<.001) and
on old adults (Mhighnegative=1.50, Mlownegative=
1.60, Mdiff =−.10, F(1, 414) =79.30,
p<.001). In short, young people are more likely
to feel fearful after reading highly negative news
than middle-aged and old adults. Interestingly,
the level of fear among middle-aged and old
adults decreased as news negativity increased.
With regard to disgust, both news negativ-
ity (F(1, 414) =9.54, p=.002, partial η2
=.02) and age (F(2, 414) =3.08, p=.047,
partial η2=.02) had significant main effects
with medium effect sizes. Middle-aged adults
(M=2.04) felt more disgusted than young
adults (M=1.78). There were no differences
between young and old adults, and between
middle-aged and old adults. There was a sig-
nificant interaction between news negativity and
age, F(2, 414) =17.90, p<.001, partial η2=
.08 (Figure 4).
Contrast analyses found that highly neg-
ative news stories had a stronger effect on
old adults (Mhighnegative=2.44, Mlownegative=
1.62, Mdiff =.82) than on middle-aged
adults (Mhighnegative=2.24, Mlownegative=1.84,
Mdiff =.40, F(1, 414) =32.71, p<.001),
and on young adults (Mhighnegative=1.52,
Mlownegative=2.04, Mdiff =−.52, F(1,
414) =89.84, p<.001).
Taken together, the above findings provide
partial support to H1, which predicted that
highly negative stories will cause stronger anger,
fear, and disgust than weakly negative stories.
Age was found to moderate the impact of nega-
tive news on the three negative emotions, but the
patterns were not consistent (RQ1).
Impacts of News Negativity and Age on
Recall and Information Seeking
The analyses revealed that only age had a sig-
nificant main effect on recall, F(2, 414) =21.32,
p<.001, partial η2=.09, with a large effect
size. Thus, H2 (Highly negative news stories on
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352 JOURNAL OF INFORMATION TECHNOLOGY & POLITICS
FIGURE 5. The moderating role of age
between news negativity and recall.
Twitter will cause better recall than weakly neg-
ative news stories) was not supported. Recall
scores were higher in the order of young adults
(M=.66), middle-aged adults (M=.62), and
old adults (M=.54). There was a significant
interaction between news negativity and age,
F(2, 414) =5.66, p=.004, partial η2=.03
(Figure 5).
Via contrast analyses, this study found
that the relationship between news negativity
and recall is moderated by age, with young
and old adults showing a significantly higher
increase of the recall score as news negativ-
ity increases than middle-aged adults (RQ1).
Highly negative news stories had a stronger
effect on young adults (Mhighnegative=.69,
Mlownegative=.63, Mdiff =.06) than on middle-
aged adults (Mhighnegative=.60, Mlownegative=
.64, Mdiff =−.04), F(1, 414) =78.56,
p<.001. Highly negative news stories exercised
a stronger influence on old adults (Mhighnegative=
.57, Mlownegative=.51, Mdiff =.06) than on
middle-age adults, F(1, 414) =8.35, p=.011.
Unexpectedly, the level of recall in the middle-
aged group decreased as news negativity
increased.
With regard to information seeking, both
news negativity (F(1, 414) =21.66, p<.001,
partial η2=.05)and age (F(2, 414) =66.07,
p<.001, partial η2=.24) had significant main
effects. Although the effect size was moder-
ate, H3 (Highly negative news on Twitter will
induce more active information-seeking behav-
ior than weakly negative news) received support.
Young adults (M=3.39) were more likely to
FIGURE 6. The moderating role of age between
news negativity and information seeking.
seek additional information about negative news
than middle-aged (M=2.71) and old adults
(M=1.83). In addition, middle-aged adults
were more likely to seek additional information
than older adults. As shown in Figure 6,there
was a significant interaction between news neg-
ativity and age, F(2, 414) =16.53, p<.001,
partial η2=.07.
Via contrast analyses, the current study
obtained the result that the relationship between
news negativity and information seeking is
moderated by age, with old adults showing
a significantly higher increase of information-
seeking behavior as news negativity increases
than young and middle-aged adults (RQ1).
Highly negative news stories had a stronger
impact on young adults (Mhighnegative=3.70,
Mlownegative=3.08, Mdiff =.62) than on middle-
aged adults (Mhighnegative=2.61, Mlownegative=
2.81, Mdiff =−.20), F(1, 414) =63.28,
p<.001. Highly negative news stories exercised
a stronger influence on old adults (Mhighnegative=
2.43, Mlownegative=1.23, Mdiff =1.20) than on
young adults (F(1, 414) =8.62, p=.010) and
on middle-aged adults (F(1, 414) =115.74,
p<.001). Unexpectedly, the level of infor-
mation seeking among middle-aged adults
decreased as news negativity increased.
Correlations between Emotions and
Recall/Information Seeking
To answer H4, H5, H6, H7, and RQ2, the
current study conducted Pearson correlation of
anger, fear, disgust, recall, and information seek-
ing. Using the Bonferroni approach to control
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Park 353
for Type 1 error across the 10 correlations, a
pvalue of less than .005 (.05/10 =.005) was
used for significance. The results show that the
correlation between fear and recall was signif-
icant, r(418) =.55, p<.001. Fear also was
positively correlated with information seeking, r
(418) =.46, p<.001. However, anger did not
have a significant correlation with either recall
(r(418) =.21, p=.052) or information seeking
(r(418) =.19, p<.059). Disgust was not cor-
related with either recall or information seeking.
Thus, H6 and H7 received support, while H4 and
H5 did not.
DISCUSSION
This study, based on the theory of nega-
tivity bias, investigated how reading negative
news stories on Twitter influences political atti-
tudes and behavior during an election cycle.
People who were exposed to highly negative
news stories on Twitter tended to feel angrier
and more disgusted and more willingly seek
information about the stories than those who
read weakly negative stories. In addition, the
current study found that age plays a moderat-
ing role in the relationship between exposure
to negative news on Twitter and negative emo-
tions, recall, and information-processing behav-
ior. In terms of anger and disgust, old adults
showed a significantly higher increase than
younger adults as news negativity increased.
Regarding fear, young adults indicated a signif-
icantly higher increase than the other two age
groups. With regard to recall, the mean change
between the two negativity conditions was sig-
nificantly higher in the young adult group than in
the other two groups. Concerning information-
seeking behavior, old adults showed the biggest
mean difference between the two negativity con-
ditions. Lastly, the current study also found that
fear is significantly correlated with recall and
information seeking.
The findings of the current study address
important theoretical implications in several
aspects. First, this study found evidence that,
in general, negativity bias can be applied
to Twitter, the leading microblogging service.
Encountering negative news stories via Twitter
triggers negative emotions (anger and disgust)
of voters, especially young adults, and moti-
vates citizens to seek more information related
to the stories. Although Twitter has unique fea-
tures different from traditional media, negativ-
ity bias was found to be applicable to Twitter.
However, it should be noted that the way neg-
ativity bias is manifested in Twitter is a little
different from that observed in traditional news
media. For instance, the means of recall and
information seeking in the middle-aged group
became smaller as news negativity increased.
Also negative news did not have a direct effect
on fear and recall. Additional studies will be
required to explain these unexpected findings.
Second, the present study revealed nuanced
mechanisms by which news negativity influ-
ences Twitter users’ negative feelings and polit-
ical learning. In particular, this study identified
age as an important variable that should be con-
sidered together with news negativity. Across
all five dependent variables (anger, fear, dis-
gust, recall, information seeking), young adults
among the three age groups showed the biggest
reaction by reporting the highest means. The dif-
ference may be because young people are not
as disengaged from the political process as we
have thought (Rheingold, 2008). Also it should
be noted that young people can be easily pro-
voked by appropriate stimuli and, as a result,
get mobilized. Considering that prior studies on
negativity bias have not considered age a critical
factor, this study’s finding is a crucial addi-
tion to the negativity bias theory. Young adults’
robust reaction to negative news is also impor-
tant in today’s media landscape, where the major
channel of news consumption is moving quickly
from traditional media to social media (Pew
Research Center, 2015).
Age was also found to moderate the relation-
ship between news negativity and five dependent
variables. For instance, young adults showed a
significantly higher increase in recall scores than
middle-aged and old adults as the news negativ-
ity condition changes from a low level to a high
level. However, the pattern of moderation by age
varied depending on each dependent variable.4
With regard to anger and disgust, old adults
experienced the biggest change between the low
negativity and the high negativity condition.
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354 JOURNAL OF INFORMATION TECHNOLOGY & POLITICS
These results suggest that in terms of negative
emotions, young adults are the most vulnera-
ble to negative news regardless of the extent
of news negativity, while old adults are the
most vulnerable to the change of news nega-
tivity. The results also indicate that in terms
of political learning and information seeking,
young adults are the most sensitive to nega-
tive news and their sensitivity gets stronger as
news negativity is heightened. Several studies
speculated that age is important in the political
involvement via social media (Bridges, Appel,
& Grossklags, 2012; Dermody, Hanmer-Lloyd,
Koenig-Lewis, & Zhao, 2014). This study finds
empirical evidence that age plays a crucial
role in how negativity bias works in social
media.
Finally, this study extends the negativity bias
theory by examining how negative feelings trig-
gered by negative news on Twitter can trans-
late into subsequent behavior. The present study
tested correlations between negative emotions
and political learning. The finding that fear is
positively related to recall and information seek-
ing, while anger and disgust are not significantly
associated with recall or information seeking,
has not been established in earlier research. The
finding may stem from the fact that fear tends to
entail systematic information processing while
anger and disgust entail heuristic information
processing (Bond et al., 2008; Tiedens & Linton,
2001). Because of such different mechanisms,
fear seems to increase attention to new infor-
mation and even boost the motivation for action
(Damasio, 1994; Lazarus & Lazarus, 1994). The
finding about the relationship between nega-
tive emotions and political learning is important
because it can extend the realm of negativity bias
to the relationship between the emotional and
cognitive responses to negative news on social
media.
This study’s findings also contain practi-
cal implications. Prior research consistently has
shown that frequent exposure to negative news
during a campaign can cause either a mobiliza-
tion or a demobilization effect (Ansolabehere &
Iyengar, 1995; Goldstein & Freedman, 2002).
This study proposes crucial evidence that nega-
tive news is more beneficial to political engage-
ment than detrimental to it. It found that
although negative news stories can arouse neg-
ative emotions, they simultaneously motivate
citizens’ political learning and additional infor-
mation seeking. This suggests the possibility
that social media, especially Twitter, function
as a participatory sphere where citizens can
have more opportunities to learn about politics
regardless of the valence of information they
encounter. Therefore, in terms of policymaking,
it would be better to secure free flow of infor-
mation including news stories on social media
rather than to restrict information flow under the
pretext that negative information harms citizens.
This study contains a few limitations. First,
inserting news stories in fake Twitter pages
might have had an impact on information pro-
cessing. Second, the findings of the current
study are not generalizable to overall social
media because this study focused only on
Twitter. Future studies need to include other
types of social media. Third, this study mea-
sured only three types of emotions. Follow-up
research can deal with other types of emo-
tions. Fourth, this study has not fully untangled
the theoretical links between emotional, cogni-
tive, and behavioral responses to negative news.
The relationship between emotion and cognitive
and behavioral reaction is complex and usually
contingent upon the intensity of the activated
emotion, and the context in which it is experi-
enced (Goodall, Slater, & Myers, 2013). Lastly,
readers should note that the positive relation-
ships reported in this study are mostly modest in
their effects, which is in line with previous find-
ings (e.g., Hansen & Kosiara-Pedersen, 2014;
Kruikemeier, 2014). Despite some limitations,
the current study makes a significant contribu-
tion to political communication by untangling
the working mechanisms of negativity bias in
the context of Twitter.
NOTES
1. Although the research background is South Korea,
the current study tried to secure external validity by recruit-
ing participants from various segments of the Korean
population.
2. See http://www.statista.com/statistics/284473/
south-korea-social-network-penetration.
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Park 355
3. Cohen (1988) has provided benchmarks to define
small (η2=0.01), medium (η2=0.06), and large (η2=
0.14) effects.
4. In some cases, the mean change between the low
negativity and the high negativity condition yielded unex-
pected results. For example, the level of fear among
middle-aged and old adults decreased as news negativity
increased. It seems that the erratic results are mainly caused
by the small sample size of this study.
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The unprecedented investment in megaprojects that has been witnessed in recent years seems likely to accelerate post Covid-19 with several countries, like Australia and the United Kingdom, announcing large infrastructure projects for economic revival. COVID-19 has also created social challenges due to increased unemployment that could result in an increase in poverty which could be helped when these projects become a reality. However, some scholars caution that rapid urbanisation and inappropriate development of infrastructure could work against containing a pandemic like COVID-19. The environmental damage caused by rapid urbanisation has prompted urban planners to rethink the ways in cities can be developed in the future. Future cities need to foster both individual and collective wellbeing, with realization of ambitions, aspirations and other immaterial aspects of life and providing contentment and happiness. How do we ensure that such aspirations are not neglected in a rush to build more infrastructure? How do we ensure that social and environmental issues will be taken into account while responding to an urgent economic need for building more megaprojects? This brings us to be concerned about how public value will be taken into account and monitored in the building of new infrastructure in post Covid-19.
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