2 Appendices - DSpace

Despite my long-term interest in the field of crisis communication, I never really had to deal
with a real crisis situation myself until 2013. During this calamity, I experienced the impact of
Twitter and the media on my organization and the public opinion. I started thinking about
which impact the media had on the tweets and the development of the situation. I wondered
how an organization could influence or control the public opinion on Twitter as soon as
possible in order to prevent the spreading of false information or own assumptions.
Furthermore, my internship in a strategic risk and crisis communication agency instigated my
interest in the field of crisis communication and management even more. As a result, when I
got to choose the subject of my bachelor thesis, I immediately thought of getting a closer look
at this aspect of crisis communication.
It is an illusion to be able to execute a research project and write the associated thesis without
the unconditional support of others. Therefore, I would like to take my time to thank a few
people. First of all, I would like to thank my promotor Pieter Soete for his critic remarks and
accompaniment during this entire process. I would not have been able to realize the same
outcomes as I actually did without the support of my promotor. Furthermore, I could not have
done this with my colleagues Hugo Marynissen and Stijn Pieters. They helped me out a lot
during my three-month internship by giving feedback on my ideas and keeping my feet on the
ground. I would also like to thank Tim Van Achte for his critical thoughts and technical
support. Together, they also changed and broadened my view on crisis and risk
communication by constantly challenging me and offering me new insights. Thank you for
that! Last but not least, I would like to thank my family and my girlfriend for constantly
putting up with my – sometimes annoying – trains of thoughts and limited availability during
the past few months. I have been partly living in a cave of papers, dictionaries and research
results, meaning I could not mentally or physically be there for them as much as I wanted to.
1
Abstracts
Dutch & French
1
Dutch
Inleiding
De niche crisiscommunicatie is tijdens de laatste decennia steeds belangrijker geworden binnen
het brede communicatiespectrum. Cases zoals het gigantische lek van BP in de Mexicaanse Golf,
Enrons schandaal of Dexia’s ondergang toonden het belang van goede crisiscommunicatie en
bewezen dat crisiscommunicatie een strategische en doordachte aanpak vergt. Ondertussen
beïnvloedt de groei van sociale media zoals Twitter de manier waarop mensen met elkaar
communiceren. Wanneer mensen via Twitter met elkaar communiceren en interageren, worden ze
door verschillende elementen beïnvloed (e.g. eigen persoonlijkheid, sociale kring, externe actoren,
etc.). Er kan gesteld worden dat de media een belangrijke impact hebben op het tweetgedrag van
mensen. Dit is vanzelfsprekend ook zo het geval tijdens noodgevallen, crises of rampen. Terwijl
organisaties of overheden via traditionele media min of meer controle hebben over de boodschap,
is dat op sociale media niet zo. Toch hebben organisaties of overheden er alle baat bij om de
boodschap in de hand te hebben.
Tijdens slechte tijden helpt social media monitoring het crisiscommunicatieteam om de omgeving
te analyseren. De social media analist helpt zo om voor een betere situational awareness te zorgen
om de situatie zo snel mogelijk onder controle te krijgen. De analisten van de Belgische en
Nederlandse overheden ontleden de omgeving volgens de IBS-methode (wat staat voor
information, behavior en sensemaking). Deze methode laat de analist toe om belangrijke
informatie vanop sociale media te distilleren en op basis daarvan een concreet advies te geven aan
het crisiscommunicatieteam én het crisismanagementteam.
Doel en onderzoeksopzet
De primaire doelstelling van deze bachelorproef is het verduidelijken van de manier waarop
nieuwswebsites en nieuwsuitzendingen het verspreiden van information, behavior en sensemaking
beïnvloeden tijdens en na acute noodsituaties en rampen. Daarnaast wil dit onderzoek inzichten
bieden over de manier waarop mensen communiceren op Twitter tijdens dergelijke situaties.
Dit onderzoek is gebaseerd op een kwantitatieve analyse en inhoudsanalyse van tweets over een
kleinschalige noodsituatie (een brand in een pitazaak) en een grootschalige ramp (een gigantische
kettingbotsing op de autosnelweg).
2
Resultaten
Het is vanzelfsprekend dat grootschalige rampen meer media-aandacht krijgen dan kleinschalige
noodsituaties. De datasets toonden daarnaast aan dat de grootschalige ramp tot meer activiteit op
Twitter leidde dan de kleinschalige noodsituatie. Men zou dus kunnen stellen dat een
grootschalige ramp meer media-aandacht krijgt, en bijgevolg meer wordt besproken op Twitter.
Tot zover erg logisch dus.
Een kwantitatieve IBS-analyse op beide datasets wees bovendien uit dat de kettingbotsing voor
veel meer sensemaking zorgde op Twitter dan de brand in Torhout. Uit de data blijkt dat vooral
nieuwsuitzendingen hierbij een belangrijke rol speelden. Dit uitte zich vooral in meer emotionele
uitlatingen over de situatie. Aan de andere kant was er erg weinig sensemaking tijdens de
kleinschalige noodsituatie, terwijl de focus van de berichtgeving op Twitter vooral op information
en behavior lag. Dit werd hoofdzakelijk gedragen door het verspreiden van nieuwsartikelen.
Conclusies
Tijdens de bestudeerde cases werd het duidelijk dat het verspreiden van nieuwsartikelen
hoofdzakelijk op information en behavior gericht is. Aan de andere kant bewees het onderzoek dat
nieuwsuitzendingen een meer emotionele respons losmaakten op Twitter, en dus meer tot
sensemaking leidden.
Voor crisiscommunicatieteams houdt dit in dat de schaal van de situatie determinerend is voor de
conversaties op Twitter over diezelfde situatie. Wanneer het over een kleinschalige noodsituatie
gaat volstaat het om kort op de bal te spelen bij media met een lage kanaalrijkdom. Op die manier
kunnen crisiscommunicatieteams de conversaties op Twitter sterk beïnvloeden en misschien zelfs
onder controle krijgen. Wanneer het echter over een grootschalige ramp gaat ligt de situatie wat
moeilijker. Tijdens dergelijke situaties zou er aanzienlijk meer aandacht gespendeerd moeten
worden aan media met een hoge kanaalrijkdom, omdat die media mensen aanzetten om een eigen
invulling te geven aan de situatie.
3
French
Introduction
La niche de la communication de crise est devenue de plus en plus importante pendant les années
passées. Des cas tels que le déversement de pétrole de BP dans la Golfe du Mexique, le scandale
d’Enron ou la disparition de Dexia ont indiqué l’importance de la communication de crise et ils
ont démontré que cette communication exige une approche stratégique et réfléchie. Pendant ce
temps, la croissance des médias sociaux comme Twitter influence la manière comment on
communique avec des autres. Quand des gens communiquent et interagissent sur Twitter, ils sont
influencés par de nombreux éléments comme notre personnalité et cercle social, des acteurs
externes, etc. On peut dire que les médias ont une influence importante sur le comportement des
gens sur Twitter. C’est évident que c’est aussi le cas pendant des urgences, crises ou catastrophes.
Pendant que des organisations ou gouvernements peuvent plus ou moins contrôler leurs messages
sur les médias traditionnels, ce n’est pas du tout possible sur les médias sociaux. De toute façon,
ils bénéficient de contrôler ces messages en tout cas.
Pendant des crises, la surveillance des médias sociaux assiste les communicateurs de crise pour
analyser l’environnement. Comme ça l’analyste aide d’obtenir une connaissance augmentée de la
situation pour gagner le contrôle aussi rapidement que possible. Des analystes des gouvernements
Belge et Néerlandais emploient la méthode d’IBS (qui représente les éléments Information,
Behavior et Sensemaking). Cette méthode permet de distiller information importante des médias
sociaux pour donner des conseils concrets aux teams de crise.
But et conception de la recherche
Le but principal de cette thèse est de clarifier la façon dont les sites web des médias et des
journaux télévisés influencent la diffusion d’information, behavior et sensemaking sur Twitter
pendant et après des urgences ou catastrophes aiguës. Cette thèse veut aussi élargir les
perspectives en ce qui concerne la manière dont on communique sur Twitter.
La recherche est basée sur une analyse quantitative et une analyse du contenu des tweets
concernant une urgence au sujet d’une petite échelle (un incendie dans un restaurant) et une
catastrophe de grande envergure (un énorme carambolage sur l'autoroute).
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Résultats
C’est évident que les catastrophes concernant une grande envergure obtiennent plus
d’attention sur les médias que des urgences au sujet d’une petite échelle. Les données aussi
démontrent que les catastrophes mènent à plus d’activité sur Twitter que des urgences. On
pourrait dire que les catastrophes de grande envergure reçoivent plus d’attention sur les
médias et sont par conséquence plus discutées sur Twitter.
Une analyse quantitative d’IBS sur toutes les données a démontré que le carambolage a mené
à plus de sensemaking sur Twitter que l’incendie et que c’est attribué aux journaux télévisés
qui ont joué un rôle primaire après le carambolage. Cela s’est traduit par des réactions
émotionnelles concernant la situation. D’autre côté, il y avait très peu de sensemaking pendant
l’incendie à Torhout, tandis que l’accent des informations a été mis sur information et behavior.
Cela s’est traduit par la diffusion des nouvelles sur les sites Web des médias.
Conclusions
Pendant les cas étudiés, c’était clair que la diffusion des nouvelles implique la diffusion
d’information et de sensemaking. D’autre côté, l’étude a démontré que l’accent des journaux
télévisés ont causés des réactions surtout émotionnelles.
Pour les communicateurs de crise, cela signifie que l’échelle d’une situation est déterminante
pour les conversations sur Twitter concernant cette situation. Quand c’est une urgence au
sujet d’une petite échelle, les communicateurs doivent agir rapidement et focaliser sur les
médias avec une richesse de canal bas. Comme ça, ils peuvent influencer les conversations sur
Twitter et peut-être les contrôler. C’est plutôt difficile quand il s’agit d’une catastrophe de
grande envergure. Pendant telles situations, les communicateurs devraient prêter attention aux
médias avec une grande richesse de canal, parce que ces médias incitent des gens à former
une propre interprétation.
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1. Literature review
8
1.1. Importance of crisis communication
9
1.1.1. Why crisis communication?
9
1.1.2. Difference between emergencies, crises and disasters
10
1.1.3. Demand for information
11
1.2. Organization of governmental crisis management and communication
13
1.2.1. Division into disciplines
13
1.2.2. Types of emergency plans
14
1.2.3. Scaling
15
1.2.4. Structures and cells
16
1.2.4.1. Proactive structures
16
1.2.4.2. Reactive structures
16
1.3. Rise of social media
17
1.3.1. Types of social media
17
1.3.2. Why Twitter?
18
1.3.3. Importance of monitoring social media during crises
19
1.3.4. Earlier Twitter research
22
1.3.4.1. Twitter’s influence on news
22
1.3.4.2. Information propagation & information cascades
24
2. Research design
26
2.1. Scope
27
2.2. Methodology
28
2.2.1. General methodology & data collection
28
2.2.2. Lapse of the Twitter activity
29
2.2.3. Information, behavior & sensemaking
31
2.2.4. Influence of news websites and news broadcasts
32
2.3. Cases
32
2.3.1. Car pile-up in Zonnebeke
32
2.3.2. Fire in a fast food restaurant in Torhout
33
6
3. Research findings
35
3.1. Lapse of the Twitter activity
36
3.1.1. Car pile-up in Zonnebeke
36
3.1.2. Fire in a fast food restaurant in Torhout
37
3.1.3. Discussion
38
3.2. Information, behavior & sensemaking (IBS)
38
3.2.1. Car pile-up in Zonnebeke
38
3.2.2. Fire in a fast food restaurant in Torhout
39
3.2.3. Discussion
40
3.3. Influence of news websites & news broadcasts
3.3.1. News websites
41
41
3.3.1.1. Car pile-up in Zonnebeke
41
3.3.1.2. Fire in a fast food restaurant in Torhout
42
3.3.2. News broadcasts
42
3.3.2.1. Car pile-up in Zonnebeke
42
3.3.2.2. Fire in a fast food restaurant in Torhout
43
3.3.3. Discussion
44
4. Conclusions
45
References
47
List of images & figures
52
Appendices
54
7
1
Literature review
An exploration of (governmental) crisis communication
and the rise of social media
8
The marriage between social media and crisis communication has its pros and cons. While it
can be argued that social media have the potential to be very powerful during crises, the past
shows that they can have major pitfalls too. For example, after a horrific car pile-up in WestFlanders during rush hour, the Belgian Red Cross asked for blood donors on Twitter in order
to be able to help the victims. In reality, this tweet had nothing to do with the accident.
However, the tweet got passed on incredibly fast, causing an excess of blood after a short
amount of time. As the popularity of social media amongst younger and older publics keeps
growing, social media are becoming important tools within the fields of marketing, recruiting
and business development (Landau, 2011). Landau argues that crisis communication is an
area that should not be overlooked when it comes to social media, as “in today’s
communication arena, social media is a venue that cannot be ignored”.
In this chapter, I explore (governmental) crisis communication and the rise of social media.
Furthermore, I discuss earlier Twitter research that lead to this thesis.
1.1. Importance of crisis communication
1.1.1. Why crisis communication?
The craft of crisis communication has been growing enormously during the last decennia.
Cases like BP’s massive oil spill, Enron’s scandal or Dexia’s downfall showed the importance
of managing crises and proved that crisis communication requires a strategic and elaborate
approach. It is safe to say that every company or organization will eventually encounter a
crisis situation that can put a big amount of pressure on that company or organization (normal
accident theory, Perrow, 1984). No matter how thoughtfully an organization’s risk
management processes are, there cannot be a plan for every possible situation (Wilcox &
Cameron, 2012).
As companies and organizations started to open their eyes to the importance of crisis
communication, the number of crises has been growing continuously. This is caused by the
growing number and complexity of technologies and increasingly scrutinizing media (Massey
& Larsen, 2006; Stephens et al., 2005).
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Furthermore, we all live in a society that demands transparency and honesty. Today’s public
even actively searches for information to satisfy their need for information (De Bas & Monté,
2012) and even spreads – sometimes incorrect – information, which can influence news
coverage and the public opinion. As a result, a strategic, transparent, multi-channel approach
of crisis communication has never been as important as it is today.
1.1.2. Difference between emergencies, crises and disasters
Emergencies, crises and disasters are often terms that are used incorrectly. While all three
have a strong negative connotation to them, emergencies, crises and disasters differ from each
other in a number of aspects.
An emergency can be seen as an unforeseen combination of different circumstances that
requires immediate action. A flooded basement, a failed operation or a power outage are
considered as emergencies. On the other hand, a disaster brings great damage, loss or
destruction. This causes serious misfortune for a lot of people of a company, city, town or
region (Jorgustin, 2012). In a way, disasters are often preceded by emergencies.
Emergencies and disasters are crisis situations, but a crisis does not necessarily have to
become an emergency or a disaster. A crisis can sometimes lead to a disaster or an emergency,
but the term crisis is much more difficult to define. It might be argued that perception plays an
important role in distinguishing emergencies, crises and disasters. Emergencies or disasters
are caused by a triggering event, such as a crash or a fire. From that point of view, there has to
be a calamitous situation physically happening in order to be able to speak of an emergency or
disaster. On the other hand, crises can occur without something physically happening. When
there is a rumor on social media that the CFO has been embezzling money, it is definitely a
crisis, but no disaster or emergency.
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During recent conversations with my former colleague Stijn Pieters, he mentioned another
way to distinguish emergencies, crises and disasters from one another. During emergencies,
all procedures and guidelines of an organization remain applicable. For example, when an
operation fails, there are a number of procedures and guidelines the hospital will follow.
During crises, however, only some of the procedures and guidelines will remain in place.
When the rumor of the CFO breaks out, procedures and guidelines will determine the crisis
communication roles in the organization, but a different, undefined approach will be
necessary to address the crisis. Finally, procedures and guidelines are insufficient during
disasters. Crisis management and crisis communications will have to reinvent themselves in
order to address the disaster. For example, if the coast line of Belgium would be hit by a
tsunami, following some procedures and guidelines would not suffice at all.
According to Bert Brugghemans & Hugo Marynissen, a distinction between fast-burning and
slow-burning situations has to be made within emergencies and disasters. Seymour & Moore
(2000) make the same distinction between ‘cobra crises’ and ‘python crises’. A fast-burning
(cobra) crisis hits suddenly and takes the organization completely by surprise, while a slowburning (python) crisis is a collection of issues that pile up.
Both the aspects of perception and ‘surprise’ play important roles in determining the way of
communicating during crises. As a result, this thesis will only focus on fast-burning
emergencies and disasters instead of covering fast-burning and slow-burning crises as well.
Hereafter, I will use the term ‘crisis’ to refer exclusively to these fast-burning emergencies
and disasters, as I will not elaborate on corporate image crises and the likes.
1.1.3. Demand for information
The demand for information during and after crises is one of the major difficulties for
communication teams. There is a constant unbalance between the need for information,
available information and necessary information to take correct operational decisions (see
figure 1-1). However, communicators need to find a way to retain the public’s trust, using
only that limited information they have at their fingertips during difficult and stressful times.
11
Very little information is available during the first moments of a crisis. Teams are operational
in the field, often trying to manage the situation, while communication lines are being set up.
Most attention is thus paid to gain control over the situation. Over time, more and more
information is being given by the teams in the field. However, the demand for information is
incredibly high during the first moments of a crisis, creating an “information vacuum”
(Marynissen et al., 2010) between available information and the demand for information.
Communication teams can fill this vacuum by giving empathic and transparent messages
containing operational information and process information.
The demand for information used to be growing slowly and remained high during a relatively
long period. New media such as social media led to a much faster and higher demand for
information than ever before, but this demand for information ironically lowers quickly. This
entails that people are no longer interested in the information when you finally managed to
gather and confirm all that information.
Figure 1-1: The demand for information during crises (Marynissen et al., 2010).
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1.2. Organization of governmental crisis management and communication
The government has several structures and processes in place to manage and communicate
about crisis situations. The Royal Decree of 2006 determines these structures and processes.
In this chapter, I discuss the outlines of the Decree in order to provide an insight in the
government’s approach to crisis management and crisis communication.
I start by explaining the division of the aid services into five disciplines. Hereafter, I elaborate
on the different types of emergency plans and the scaling of crisis situations. Last, I will
discuss the formal governmental structures.
1.2.1. Division into disciplines
The aid services are divided into five disciplines. Each discipline has its own tasks and
responsibilities. I will now explore the different disciplines without elaborating much on the
structures and processes within each discipline.
Discipline 1:
In contradiction to what many people think, firemen have a lot more
Fire department
responsibilities during crises situations than just extinguishing fire.
The fire department’s task during crises is to manage the situation and
eliminate all possible risks that are connected to that situation. They
take care of searching and liberating victims, if any.
Discipline 2:
The medical services take medical and psychosocial care of the
Medical services
victims once they have been located and evacuated. They also
organize the transport of the victims to near hospitals and have to take
measures to ensure the public’s health.
Discipline 3:
The police’s responsibilities mainly consist of maintaining the public
Police
order and installing and guarding the perimeters. Furthermore, the
police take care of evacuating citizens, identifying victims and
assisting with the official investigation.
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Discipline 4:
The civil protection sometimes enforces the other disciplines by
Logistic support
supporting them logistically (e.g. with sand bags, pumps, vehicles,
etc.). Operational teams of the civil protection often join discipline 1.
Discipline 5:
The task of the fifth discipline is to inform the citizens. During crises,
Information
the communication department of the town in which the crisis takes
place forms this discipline. This can cause communication problems,
as the local communication functionaries are often not prepared to
address large-scale crises. That is why the Belgian government has
recently established “Team D5”, a group of communication
professionals who can reinforce local communication functionaries
when they cannot handle the situation by themselves. The idea behind
“Team D5” is that local communication functionaries should be able
to ask for reinforcements, just like firemen and policemen can.
1.2.2. Types of emergency plans
In order to ensure an effective collaboration, emergency plans are drafted. Generally, there are
three types of emergency plans: internal emergency plans, monodisciplinary emergency plans
and multidisciplinary emergency plans.
Internal
Large companies have internal emergency plans ready in case
emergency plans
something happens. They contain evacuation procedures, contact lists,
roles within the crisis teams, and so on. However, not all companies
are required to have an internal emergency plan in place.
Monodisciplinary
Each discipline has its own emergency plans (e.g. medical
emergency plans
intervention plan). These plans are used when there is no need for a
complex interdisciplinary approach.
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Multidisciplinary
Multidisciplinary emergency plans ensure an effective collaboration
emergency plans
between disciplines. On the one hand, there are general emergency
and intervention plans (Dutch: ANIP) that describe general processes
and guidelines to manage crises. On the other hand, special
emergency and intervention plans (Dutch: BNIP) complement general
plans with additional information and guidelines concerning certain
risks when necessary (e.g. railway accidents, nuclear accidents, etc.).
1.2.3. Scaling
There are three levels of crisis management in Belgium: the municipal, provincial and
national level. The level of crisis management is generally being determined by a combination
of elements, such as geographic location, number of victims, facts, nature of the crisis, etc.
Each level enables a number of corresponding structures.
It is necessary to mention that not all crisis situations have to be scaled up to one of the levels.
For example, fire departments will take care of a barn fire on their own, without coordination
of the mayor or the help of communication functionaries. In that case, the highest ranked
fireman at the scene will address the press if necessary.
A situation is being scaled up to the municipal level when a municipal approach is necessary,
such as floods and gas leaks. The mayor promulgates this level in consultation with the
governor and coordinates the crisis. Municipal communication functionaries take care of the
communication. Additionally, the municipal coordination committee (Dutch: GCC) is being
activated and led by the mayor. The provincial level is being promulgated when the situation
includes multiple municipalities or when the governor needs to coordinate the crisis. The
governor promulgates this level in consultation with the minister. While the municipal
coordination committees remain active, a provincial coordination committee (Dutch: PCC) is
being activated and led by the governor. Municipal and provincial communication
functionaries take care of the communication. A crisis is being scaled up to national level
when one or more provinces are involved, or when the governor does not have adequate
resources available to address the situation. The Minister of Internal Affairs promulgates and
coordinates the national level. The coordination committees remain active.
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1.2.4. Structures and cells
Hereafter, I explore the formal structures and cells of governmental crisis management. I
hereby make the distinction between proactive and reactive structures, as some structures are
activated after a triggering event whereas some of them work proactively.
1.2.4.1. Proactive structures
On municipal and provincial level, safety cells are coordinated and led by respectively the
mayor and the governor. The tasks of these safety cells include (but are not limited to)
preparing risk analyses, creating crisis plans, organizing crisis exercises, analyzing previous
crises, and so on. Every discipline has a representative in the cell. The functionary for
emergency planning also joins the cell. On a federal level, there is a departmental crisis cell
for each federal public service. Its tasks are similar to the safety cells’ tasks. In addition, the
departmental crisis cells coordinate the contact between the crisis center of the government
and the department concerned.
1.2.4.2. Reactive structures
The operational coordination in the field is in the hands of the CP-OPS (command post
operations). The CP-OPS is led by the fire officer (Dir-CP-Ops) and joined by the directors of
each discipline. The municipal and/or provincial coordination committees take care of the
strategic coordination of the situation. These committees evaluate the situation continuously,
advise the mayor or governor, organize the information and impose measures. The
coordination committee is led by the mayor or governor and consists of representatives of
each discipline, the functionary for emergency planning and experts, if necessary. On a
federal level, there is no coordination committee. When the federal phase is promulgated,
three different structures are being activated within the coordination and crisis center of the
government:
 The evaluation cell consists of experts and evaluates the situation continuously.
 The policy cell consists of involved Ministers and imposes measures.
 The information cell consists of communication officials and takes care of the
situation.
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1.3. Rise of social media
Social media form a group of diverse and fast developing communication media. They enable
the production and sharing of information through collaborative means. Social media are
everywhere. That is clear.
These – relatively new – media can be described as “the collective of online communications
channels dedicated to community-based input, interaction, content-sharing and collaboration”
(Rouse & Wigmore, 2012). They are immediate, ubiquitous and available (Landau, 2011).
Since the year 2000, different social media started to emerge and gain popularity surprisingly
fast. The slow shift to these online media had its impact on the way of communicating and
interacting with each other (Qualman, 2010).
1.3.1. Types of social media
On his blog, Tim Grahl comprehensively mentions six types of social media: social networks,
bookmarking sites, social news sites, media sharing sites, microblogging sites and blogs.
Social networks
Social networks enable users to build a profile and connect with
other people they might or might not know. The platform facilitates
and encourages interaction between users. Facebook and LinkedIn
are the most commonly known social networks.
Bookmarking sites
Bookmarking sites are usually less known than social networks.
These sites allow users to save and manage their links.
StumbleUpon is one of the major bookmarking sites.
Social news sites
Social news sites allow users to post links to external news articles.
Other users then vote for their favorite articles, creating a virtual
stream of articles that consists of the articles that got the most votes.
Reddit is an example of a social news site.
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Media sharing sites
Media sharing sites enable users to post and share their own media
content. Mostly, people can make profiles, rate each other’s content
and interact. YouTube is one of the major media sharing sites.
Microblogging sites
Microblogging means blogging on a very small scale. Users can
create profiles and post short messages. Interaction is an essential
aspect of microblogging. Twitter is the major microblogging site.
Blogs
A blog is a website on which a user posts messages, pictures or
video footage. This might be a personal message or a message
concerning a certain topic. Users are able to comment on each
other’s posts. Wordpress is one of the major blogging platforms.
1.3.2. Why Twitter?
This thesis focuses on the microblogging platform Twitter. Twitter enables microbloggers to
post tweets, which are short posts of up to 140 characters in length. Twitter goes back to the
basics of communication: sending information, receiving information and giving feedback.
Despite the fact that Twitter is a relatively small platform in comparison to Facebook, it sure
is one of the most influential social media. According to a recent article posted on Digital
Marketing Ramblings, there are 1.23 billion Facebook profiles while Twitter only has 243
million monthly active users (Data from March 2014).
Although Facebook does not have a growth problem, an article from 2011 in the Guardian
(Filloux, 2011) states that “Facebook’s usage is undergoing a split” Whereas intense
Facebook users are showing more engagement to the platform, more and more ‘regular’ users
are becoming increasingly careful and reluctant. According to the blogger, this is due to a
number of factors, such as the advertising-driven business model and the more complicated
interface of Facebook. The microblogging platform has a much simpler interface, less direct
ads and less ‘noise’, since relations do not have to be reciprocal. Furthermore, people actively
follow someone on Twitter because they are actually interested in what that person shares.
18
On the other hand, Facebook users’ news feeds are filled with ‘throw-on-my-Facebook-wall’
content by people they often even do not know. All these elements slowly lead to a change of
mindset. Other social media benefit from this changing mindset. Especially Twitter.
1.3.3. Importance of monitoring social media during crises
What is monitoring?
Literature describes social media monitoring as a specific research approach that covers both
the collection of data and data analysis (Ruggiero & Vos, 2014). While Branthwaite &
Patterson (2011) stated that monitoring is observational, passive and quantitative, it could be
argued that social media monitoring contains an important qualitative aspect (cfr. infra).
Bengston et al. (2009) designate Alvan Tenney as the ‘founding father’ of monitoring. He
proposed to measure the ‘social weather’ back in 1912, long before social media even existed.
Why monitoring?
The general goal of social media monitoring is analyzing the environment (Zailskaite-Jakste
& Kuvykaite, 2012). Monitoring might in particular be very important during ‘hot times’,
such as emergencies, crises or disasters. During calamitous situations that are unpredictable,
unknown and fear-inducing, the importance of gaining fast insights into public perceptions
and information needs becomes evident (Sheppard, 2011). It could be a manner to detect early
signals, receive requests for assistance or establish better situational awareness. During ‘cold
times’, social media managers could monitor to identify radical opinions (Yang et al., 2011),
profile criticism (Keelan et al., 2010) or negative information (Campbell et al., 2011). In this
aspect, social media monitoring definitely has a qualitative part to it. Executing a single
quantitative analysis will not suffice during calamitous situations.
Some organizations realize the importance of social media monitoring and use it to their
advantage as much as possible. For example, Antwerp Fire Officer Bert Brugghemans
embraces these ‘small data’ to gain maximum insight in the situation in the field before
firemen even reached the scene.
19
A recent post on Bert’s blog showed how he managed to find pictures on Twitter of a bus on
fire, enabling him to form a very clear picture and understanding of what was happening on
the scene. In this case, social media monitoring does not only help crisis communication
teams to measure the ‘social weather’. It also allows crisis management teams to obtain better
situational awareness in order to gain control over the situation.
Role of monitoring in the crisis communication team
The person or team who is monitoring social media is usually a part of the bigger monitoring
team. In case of large disasters, other people could assist the monitoring team by monitoring
radio, television, news websites and papers. However, usually one person takes on these tasks:
the analyst. The risk and crisis communication agency PM established clear roles within the
crisis communication team. The analyst gathers, curates and visualizes information, adding
his own advice to the analysis as he knows better than anyone what is going on in people’s
minds. Everything the crisis communication team does is based on what the analyst said. In
that aspect, the analyst is the engine of the crisis communication team, as he lays the
foundations for an effective communication strategy.
Information, behavior and sensemaking (IBS)
The literature concerning monitoring generally makes the distinction between researcherdriven analysis on the one hand and computerized content analysis techniques on the other
hand (Ruggiere & Vos, 2014). Obviously, the researcher plays a central role in researcherdriven analysis. In this method, the analyst performs a search on social media and examines
the search results based on content or discourse. Next to researcher-driven analysis,
computerized content analysis uses software (e.g. WordStat) to detect trends, main topics,
personality dimensions, etc. Each monitoring method has its pros and cons. Researcher-driven
analysis enables the analyst to examine the qualitative data carefully but requires a lot of time
and focus, whereas computerized content analysis often is much faster but less nuanced. It
could be argued that the type of crisis determines the most suitable type of analysis.
20
Analysts of the Belgian and Dutch governments distill valuable information using the IBSmethod, which is a researcher-driven analysis on both content level and discursive level. IBS
stands for information, behavior and sensemaking. The idea is simple: the analyst compiles
everything concerning information (e.g. there has been an explosion), behavior (e.g. people
are running down the streets) and sensemaking (e.g. people are comparing the explosion to
the events of 9/11). The method enables the analyst to take a closer look at the information
and enrich the information in order to give good advice to the operational teams.
The IBS-method goes a little further than classic content analysis. The method analyzes
general topics and trends as well, but also distinguishes three additional levels: information,
behavior and sensemaking. Using the IBS-method, analysts are able to gather all operational
information as well as concerns and emotional responses, making sure that all the useful
information is being distilled out of the data.
Figure 1-2: IBS-analysis executed during a recent bomb threat in Antwerp.
It could be argued that there is a thin line between information and behavior. Information
generally stands for operational information, whereas behavior implies what people are doing
in the field. Behavior could thus be considered operational information too. Following this
reasoning, information and behavior are completely objective. On the other hand,
sensemaking is obviously subjective, as people add emotional value when trying to make
sense of a crisis situation. As a result, this research grouped information and behavior and
opposed them to sensemaking.
21
1.3.4. Earlier Twitter research
So far, I have already described the importance of crisis communication, the organization of
governmental crisis management and communication and the rise of social media. I have
elaborated on the difference between emergencies, crises and disaster. I also clarified the
goals of social media monitoring and the role of social media monitoring within the crisis
communication team. In this section, I provide a deeper insight in the use of Twitter and how
people communicate on Twitter, by reviewing past research and literature on the matter. I
hereby focus on the influence of Twitter on journalism and news. I also elaborate on basic
information cascade and information propagation principles.
1.3.4.1. Twitter’s influence on news
Breaking the news
As stated earlier, everyone is a journalist these days (Breakenridge, 2012), since anyone can
be a publisher now (Shirky, 2008). Everyone is able to communicate with one another, as 91%
of all people on earth have a mobile phone. But in today’s society, a regular mobile phone is
not sufficient anymore. 56% of all people on earth own smartphones. The shift to
smartphones now enables the self-declared journalist to spread all kinds of information
through a variety of platforms, media and networks. Pictures and videos are available on the
internet faster than ever. Furthermore, people are getting more and more attached to their
mobile devices, often leading to a so called smartphone addiction (Archer, 2013). Archer
argues that our mobile devices have not just become objects, but for many of us a best friend.
When it comes to the use of Twitter, the shift to smartphones and online media is almost
causing an automatic reflex to tweet when something happened. For instance, when the
Asania Airlines flight OZ2014 crashed on the runway in San Francisco, the first tweet (and
picture) was posted only 30 seconds after the crash. This tweet broke the news and started a
conversation on Twitter that got picked up fast by news media. Another great example is the
emergency landing of the US Airways flight 1549, which landed in the Hudson River in New
York (January, 2009). Two minutes after the crash, the first tweet was posted. Photos of the
watery landing were posted five minutes after the crash.
22
News media recently recognized the value Twitter holds for them. Journalists have been
involved in a wide discussion about the meaning of the people formerly known as the
audience during the past 10 years (Rosen, 2006). For example, instead of sending an in-house
photographer to the scene of an accident, news media could crowdsource footage from the
scene. Vehkoo (2013) states that “the web has lowered the barrier for co-operation in tasks
that would previously been executed by professionals”. Beckett (2008) further argues that
contemporary journalists are facilitators instead of gatekeepers. By embracing crowdsourcing,
the process becomes faster and the information sticks around longer (Beckett, 2008). In
Belgium, the process of crowdsourcing footage keeps gaining popularity amongst news media.
VTM launched the newswire ‘4040’ in 2005, enabling people to send own content
immediately to the redaction. In addition, news media regularly ask for footage right away
through their social media accounts.
News media should keep an eye on the pitfalls that crowdsourcing entails. Self-declared
journalists are mostly “web users who are not professional journalists, contributing directly to
the production of the daily news” (Ruellan, 2007). Citizen journalists thus lack formal training
in journalism, meaning they do not feel obliged to be fair and unbiased in their reporting
(Landau, 2011). It could be argued that crowdsourcing implies putting more work into
ensuring the quality of journalism.
Eventually, every journalist faces an existential crisis: what is it that professional journalists
can do that others cannot? (Vehkoo, 2011). It might be argued that place and time are crucial.
By using the crowd, Belgian news redactions now have 11 billion journalists available in
every part of the country, ready to deliver news stories as they happen.
Bringing & spreading the news
Most traditional news outlets have a social presence (Stassen, 2010). While these news outlets
use social media to bring their information to the public, journalists use social media to gather
news (Garrison, 2003, Hermans et al., 2009). Traditional news media use social media as
sources and vice versa. Landau (2011) states that the “inter-reliance of social media and
traditional media creates a vast and fast information-sharing network and news community.
Additionally, many media mention Twitter in their news coverage and a majority of
journalists even use it as a source (Cision & GWU, 2009).
23
When it comes to spreading the news, Handy (2012) indicated that people retweet information
when they think the tweet is going to resonate with their followers. Handy states that “a
retweet is like retelling someone else’s joke.” “Sure, you found the joke funny when you
heard it the first time. But you are retelling it to someone new because you think they will find
it funny.”
Earlier research showed that, of all social media, Twitter has the edge in promoting news
content. While Facebook remains a solid referral to news stories, Twitter’s referrals are of a
whole different (i.e. more intense) nature. It might be argued that spreading information
concerning emergencies, crises and disasters is easier than spreading positive news or maybe
even sports news, due to the human nature. Our brains are evolutionary trained to seek out
news of dramatic, negative events. Neuroscientists say that “our brains evolved in a huntergatherer environment where anything novel or dramatic had to be attended to immediately for
survival” (Williams, 2010). We do not have to defend ourselves against wild animals anymore
these days, but our brains have not caught up with our way of life.
During crisis situations, people may choose to share information regardless of their
geographical location. Generally, people who are close to the crisis event will retweet more
specific and locally-relevant information. People who are not close to the event will retweet
more broad information (Vieweg et al., 2010). Other factors such as personal characteristics,
involvement and the scale of the calamity are determinative for the spread of information too.
1.3.4.2. Information propagation & information cascades
Many researchers have focused on quantitative research to take a closer look at the way
information flows on Twitter in order to define so called information propagation models or
information cascade models. Information propagation is the act of spreading own information
or information from someone else through your own network. Information cascades occur
when people engage in the same acts as someone else, despite possible contradictions
between those acts and private information (Easley, 2010).
24
In the case of Twitter, information cascades happen when people retweet messages of
someone else, despite information or possible bias of their own. In this thesis, I will not
elaborate on the mathematical models concerning information propagation and information
cascades. I will, however, dig a little deeper into Twitter use during crisis situations and the
lifespan of URL’s and hashtags.
Hui et al. (2012) found that, during emergencies or crisis events, information cascades tend to
be wide, reaching a large audience, but not very long. Most retweeted messages only got
retweeted once, thus ending the short cascade. They also stated that people mostly tend to
retweet messages from reliable sources or people with a high in-degree; i.e. people who can
provide valuable information. In their case study, Hui et al. revealed that local media users
and certain key players within the community got retweeted the most.
Sadikov & Martinez (2010) executed research on the lifespan of URL’s and hashtags in
information cascades on Twitter. They proved that external sources have a significant
contribution to the propagation of URL’s and hashtags. Furthermore, they stated that hashtags
form relatively large cascades, that start merging into one giant cascade over time, while
URL’s travel a way shorter distance in smaller cascades. Additionally, Sadikov & Martinez
found that “the probability of a tag is directly related to the number of neighbors who already
adopted [the tag] and the strengths of ties with them”. This is not the case for URL’s.
25
2
Research design
26
2.1. Scope & research question
As aforementioned, communicating during crises is essential for companies as well as
governmental bodies. Companies communicate to inform their stakeholders and to prevent or
limit image damage. Governmental bodies communicate to inform citizens so they maintain
the public’s trust during and after the crisis. To do so, it is essential for them to understand the
way people communicate before they start to communicate themselves. This is also the case
on social media such as Twitter.
As people communicate differently depending on which medium they use, social media in
general – and specifically Twitter – entail different communication properties. In addition to
countless cases in the past, Schultz, Utz and Goritz (2011) already proved that Twitter pages
can be very effective means for crisis communication. When communicating via Twitter,
however, people are being influenced by a number of elements, such as their own personality,
social circle and external actors. It could be argued that news media have a major influence on
the way people communicate. They create news articles, discuss events and distribute images
and video footage. As a result, the influence of news media on Twitter during calamitous
situations is an interesting research topic.
The main goal of this thesis is to clarify the way people spread information, behavior and
sensemaking during crises. It tries to measure the influence news websites and news
broadcasts have on the use of Twitter during these situations. The underlying purpose is to
provide social media analysts information concerning the use of Twitter during crisis
situations. The following research question was set:
What is the influence of news websites and news broadcasts on the spread of information,
behavior and sensemaking on Twitter during and after fast-burning emergencies and
disasters?
27
2.2. Methodology
2.2.1. General methodology & data collection
The research is based on Twitter data from two cases, leading to a combination of a case
study, content analysis and a quantitative approach to the data.
In order to optimize the reliability of the research, I chose two totally different situations.
However, the chosen events had to meet certain predetermined criteria. First of all, the usage
of Twitter is entirely different in various countries. This is due to factors like population,
cultural background, availability of technology, geographical location, and so on. The
research focused on crises that happened in Flanders, Belgium. Furthermore, I chose crises of
a different order of magnitude. In Belgium emergencies and disasters can be scaled up to a
municipal, provincial and national phase. Since the national phase is hardly ever promulgated,
I chose a provincial disaster and an emergency that was not scaled up at all.
The most essential part for the research was getting data sets. Since Twitter’s archive is not
available for the public, another way to get the data had to be found. Different ways were used
to capture the data, entailing I had to make sure that all the data met the same requirements in
order to conduct reliable research. The tweets from the car pile-up in Zonnebeke1 and the fire
in Torhout (cfr. infra) were collected using Twitter’s search API (application programming
interface). In general, it is possible to retrieve all tweets containing a key word or hashtag up
to approximately seven days in the past. However, Twitter is not able to show all tweets with
that key word or hashtag that were posted before those seven days. Only a small percentage
(about 10 percent) will be available, depending on your own followers list, interactions and
profile. When the car accident happened in Zonnebeke, all tweets about the accident with the
hashtags #kettingbotsing and #A19 were collected. When the fire in Torhout started, all
tweets containing the key words or hashtags “brand torhout”, “brand pitazaak”, “pitazaak
torhout”, “brand pitabar”, “pitabar torhout”, “inferno torhout”, “inferno pitabar”, “inferno
pitazaak” and “brand #torhout” were retrieved. Since the fire in Torhout had a smaller reach
than the car accident in Zonnebeke, I had to base my dataset on more key words and hashtags.
1
Dutch researcher Harro Ranter collected these tweets. Via my internship, I got access to the data.
28
2.2.2. Lapse of the Twitter activity
By examining the lapse of the Twitter activity, I tried to gain insight in when and how people
tweet the most after crises. I tried to answer the following questions. How long does it take for
the Twitter activity to reach is maximum? During which time periods do people tweet the
most? What could influence the Twitter activity? How long do people keep tweeting about a
crisis? Which types of tweets (cfr. infra) do people post the most, and when do they do it?
In order to track down the evolution of the Twitter activity, time periods of half an hour were
used to group the data. These time periods made it possible to visualize different data
throughout the period after the events. Furthermore, I had to assign certain labels to different
types of tweets. I used the following distinction:
Original tweets (hereafter
A tweet is labelled as an original tweet when the user added
referred to as OT’s)
own value to the tweet. Both “regular tweets” (e.g. when you
take out your smartphone and send a tweet) and replies are
considered original tweets, since the user adds own value to
the message instead of merely passing on information.
Following this reasoning, cited retweets or shares (cfr. infra)
are also labelled as original tweets.
29
Retweets (hereafter
Tweets are labelled as retweets when a user retweets messages
referred to as RT’s)
from other users without adding own value. In that case, the
user just passes on the message.
Shares
All news sites have social media functionalities these days.
When reading an article online, there is always a sharing menu
that enables the user to share the article on social media. When
doing this, a standard sentence is automatically added to the
tweet. The tweet also links to the article. Only when a user
does not add own value to the link, the tweet is considered as a
share. Following the past reasoning, a shared article combined
with added value by the user is labelled as an original tweet.
30
2.2.3. Information, behavior and sensemaking
As aforementioned, there is a thin line between information and behavior, as they are both
strictly objective in contradiction to sensemaking, which is strictly subjective. I therefore
chose to group information and behavior on the one hand and keep sensemaking on the other
hand.
By analyzing information, behavior and sensemaking I tried to gain insight in the general tone
of the communication after crises, since a predominantly emotional (subjective) tone requires
a different approach to crisis communication in comparison to a predominantly objective tone.
I hereby tried to answer the following questions. Do people predominantly tweet objective or
do they mostly react emotionally? During which time periods do people tweet the most
objective or subjective? What influences information and behavior on the one hand, and
sensemaking on the other hand?
I executed a content analysis on the collected tweets of both crises, labelling every tweet as an
IB-tweet (information and behavior) or an S-tweet (sensemaking). I did not label tweets as
both IB-tweets and S-tweets, since a tweet is in any case subjective when there is
sensemaking, even if it has information and behavior in it. The same time periods of half an
hour as mentioned before were used to group the data. Some examples:
Information & behavior
Sensemaking
31
2.2.4. Influence of news websites and news broadcasts
By analyzing the influence of news websites and news broadcasts, I tried to gain insight in the
way they could be applied to influence conversations on Twitter. I hereby tried to answer the
following questions. How much of the tweets contain links to news articles? Do people
merely share articles or do they add own value? Do people tweet differently during news
broadcasts? What is the influence of news articles and news broadcasts on information,
behavior and sensemaking?
To analyze this influence of news websites on Twitter during fast-burning crises situations, I
executed a quantitative research on the data by checking how many tweets contained a link to
an article on the one hand and how many tweets were sent automatically by sharing a news
article on the other hand. Furthermore, I examined possible changes in the lapse of the Twitter
activity and information, behavior and sensemaking during news broadcasts.
2.3. Cases
2.3.1. Car pile-up in Zonnebeke (December 3, 2013)
At the end of 2013, thick fog caused a gigantic car pile-up on the A19 highway in Zonnebeke
(West Flanders, Belgium) around 10 o’clock in the morning. Two people died in the accident,
and more than 130 cars were involved in the accident. Furthermore, 68 more commuters got
injured, some of them heavily. The emergency services immediately closed the freeway for
the entire day. The biggest issue for the emergency services was the fact that a lot of the
victims were stuck in their vehicles. Together with the Red Cross, the firemen installed a field
hospital to help the victims.
The provincial phase was promulgated for a few hours in order to gain control over the
situation as soon as possible. The provincial phase got called off around 15 o’clock in the
afternoon. Additionally, the newly established “Team D5” (Cfr. supra) reinforced the local
communication functionaries. The events of December 3 got widely covered in local, national
and even international media, making the hashtag #A19 trending in Belgium.
32
Image 2-1: The car accident resulted in a horrific pile of twisted steel.
2.3.2. Fire in a fast food restaurant in Torhout (April 1, 2014)
On April 1, three-year old twins accidentally caused a fire in the fast food restaurant of their
parents in Torhout. When the parents noticed the fire and went upstairs to rescue their
children, the twins were already unconscious. They were quickly transported to the hospital,
where one of them died during the night. His brother sadly died the next day. Other customers
were overcome by toxic smoke and had to be treated. A lot of people followed the actions of
the emergency services from a distance. One of them was a journalist, who was able to break
the news to his redaction.
This crisis did not get scaled up to the municipal level. In this case, the highest ranked fire
officer at the scene spoke to the press on the scene. At a later stage, the Prosecution Counsel
started the official investigation and communicated about the development of the situation
and the investigation.
33
Image 2-2: Emergency services blocked the street for a while in order to take care of the
victims.
34
3
Research findings
35
3.1. Lapse of the Twitter activity
3.1.1. Car pile-up in Zonnebeke
At 9:41 o’clock, the first tweet about the car accident was posted. As this was a big disaster
(that got scaled up to a provincial phase at some point), there immediately was a lot of media
coverage. 3701 tweets were captured over a time period of 12 hours.
450
400
Tot.
350
RT's
Shares
OT's
300
250
200
150
100
50
0
Figure 3-1: Twitter activity concerning the car pile-up in Zonnebeke.
The first peak in the Twitter activity reaches its maximum around 11:30 o’clock in the
morning (see figure 3-1). The peak is being caused by people retweeting messages. When the
media broke the news, people started sharing news articles too. At that point, a smaller part of
the tweets were original tweets. Around 2:00 o’clock, the first peak was over. That moment
marked the beginning of a period with relatively low Twitter activity concerning the accident.
During that period, there were more retweets than shares and more shares than original tweets.
Around 18:30 o’clock, there is a second peak visible. Most tweets were original tweets during
that peak. Furthermore, there clearly were more shares than retweets. In that aspect, the
second peak is totally different in comparison with the first one. The peak ends around 20:00
o’clock.
36
3.1.2. Fire in a fast food restaurant in Torhout
Since the fire in Torhout was a crisis on a relatively small scale, I chose to analyze a longer
time period in order to be able to retrieve enough data to conduct reliable research.
Furthermore, there still was a child who got fatally wounded during the fire. The child sadly
died the next day. Those tweets were also included in the data set. 300 tweets were captured
over a time period of approximately 22 hours.
45
40
Tot.
RT's
Shares
OT's
35
30
25
20
15
10
5
0
Figure 3-2: Twitter activity concerning the fire in Torhout.
When the fire started to burst out, the first tweets were sent by people who were near the
situation (see figure 3-2). During this phase, retweets caused the peak in the Twitter activity.
When the first articles appeared on websites and social media of the local and national news
media, sharing those articles exceeded retweeting tweets. From that point on, almost every
peak in the Twitter activity was caused by people sharing articles. There are clearly three
peaks visible. The first peak is caused by people breaking the news (cfr. supra) by retweeting
and sharing articles (20:55-01:00 o’clock). The second one is caused by a press release saying
that the fire was not alight intentionally (11:00-13:00 o’clock). The last peak is caused by the
news that the second child had died in the hospital (15:00-17:00 o’clock).
37
3.1.3. Discussion
The Twitter activity concerning a calamitous situation reaches its maximum quickly after the
events. Additionally, the research showed that the first peak is generally caused by people
wanting to spread and share information. This is mostly reflected in people retweeting others.
People then tend to form less messages of their own, as they prefer spreading and sharing
information during that stadium. Furthermore, the research showed that the amount of original
tweets, retweets and shares generally converged after the car accident in Zonnebeke, whereas
the Twitter activity of the fire in Torhout almost exclusively consisted of shares.
Figure 3-3: The first peak in the lapse of the Twitter activity is generally caused by people
wanting to spread and share information.
3.2. Information, behavior & sensemaking (IBS)
3.2.1. Car pile-up in Zonnebeke
Immediately after the accident, there clearly were more tweets related to information and
behavior than tweets related to sensemaking. The amount of sensemaking gradually increased,
whereas the amount of information and behavior gradually lowered. Additionally, there are
two time periods during which the curve shows a surprising deviation, i.e. between 12:00 and
13:30 o’clock and between 18:00 and 20:30 o’clock. The black lines are trend lines,
intersecting each other during between 18:30 and 19:00 o’clock.
38
100,00%
I&B
S
90,00%
80,00%
70,00%
60,00%
50,00%
40,00%
30,00%
20,00%
10,00%
21u11 - 21u41
20u41 - 21u11
20u11 - 20u41
19u41 - 20u11
19u11 - 19u41
18u41 - 19u11
18u11 - 18u41
17u41 - 18u11
17u11 - 17u41
16u41 - 17u11
16u11 - 16u41
15u41 - 16u11
15u11 - 15u41
14u41 - 15u11
14u11 - 14u41
13u41 - 14u11
13u11 - 13u41
12u41 - 13u11
12u11 - 12u41
11u41 - 12u11
11u11 - 11u41
10u41 - 11u11
10u11 - 10u41
9u41 - 10u11
0,00%
Figure 3-4: Visualization of the ratio between the percentage of IB-tweets and S-tweets
concerning the car pile-up in Zonnebeke.
3.2.2. Fire in a fast food restaurant in Leuven
When labelling the tweets as IB-tweets and S-tweets, it became clear that there hardly was
any sensemaking on Twitter during and after the fire. People especially posted messages
related to information and behavior. When looking at the curve, there is one peak visible.
However, that peak is not representative, since there only was one tweet sent during that time
period. That tweet just happened to be an S-tweet. There were no tweets posted during the
time periods where the curve is interrupted. The black lines are trend lines.
39
120%
100%
80%
60%
%IB
%S
40%
20%
0%
Figure 3-5: Visualization of the ratio between the percentage of IB-tweets and S-tweets
concerning the fire in Torhout.
3.2.3. Discussion
The research showed that the scale of the studied situations determined the amount of
sensemaking on Twitter. Following this reasoning, it could be argued that major crisis
situations will lead to more sensemaking, while minor crisis situations will lead to more
messages related information and behavior. Generally, the amount of sensemaking gradually
increases over time, while the amount of information and behavior gradually lowers.
The amount of information, behavior and sensemaking remains more or less stable over time
during minor crisis situations. In contrast, the amount of information, behavior and
sensemaking during major crisis situations evolves quickly. In that case, information and
behavior are gradually being replaced by sensemaking. This might be explained by the lapse
of the Twitter activity (see 3.1.: lapse of the Twitter activity). When disaster strikes, people
tend to spread and share information to break the news. As a result, this often is operational
information – and thus related to information and behavior. Over time, people will have
received all operational information that is available. This could give people the space to
interpret all the information and form their own opinions and evaluations.
40
3.3. Influence of news websites & news broadcasts
3.3.1. News websites
3.3.1.1. Car pile-up in Zonnebeke
Of all 3701 collected tweets, a total of 1612 tweets (43%) contained a link to a news article.
773 tweets (21%) were directly posted via news website by sharing news articles. The user
did not add any value to these tweets. Of all 1991 retweets, 698 tweets (35%) contained links
to news articles. While the percentage of retweets that contain links remains more or less
stable all the time (around 35%), the curve shows a clear kink in the curve between 18:00 and
20:00 o’clock. It might be argued that this was being caused by the news broadcasts at that
time (see 3.3.3.: news broadcasts).
80%
70%
60%
50%
40%
30%
20%
10%
21u11 > 21u41
20u41 > 21u11
20u11 > 20u41
19u41 > 20u11
19u11 > 19u41
18u41 > 19u11
18u11 > 18u41
13u41 > 14u11
17u41 > 18u11
13u11 > 13u41
17u11 > 17u41
12u41 > 13u11
16u41 > 17u11
12u11 > 12u41
16u11 > 16u41
11u41 > 12u11
15u41 > 16u11
11u11 > 11u41
15u11 > 15u41
10u41 > 11u11
14u41 > 15u11
10u11 > 10u41
14u11 > 14u41
9u41 > 10u11
0%
1
2
3
4
5
6
7
8
9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
Figure 3-6: The percentage of retweets that contain links to news articles reaches its lowest
point between 18:00 and 20:00 o’clock.
41
3.3.1.2. Fire in Torhout
Of all 300 collected tweets, a total of 259 tweets (86%) contained a link to a news article. 187
tweets (62%) were directly posted via news website by sharing news articles. The user did not
add any value to these tweets. Of all 74 retweets, 59 tweets (80%) contained links to news
articles.
3.3.2. News broadcasts
3.3.2.1. Car pile-up in Zonnebeke
The car pile-up in Zonnebeke got covered the more by news media than the fire in Torhout.
During the studied time period, there were four news broadcasts: at 12:00, 13:00, 18:00 and
19:00 o’clock. The news broadcasts at 12:00 o’clock were extra broadcasts by VTM and Een.
Firstly, there is a clear link visible between the peaks in the Twitter activity and the news
broadcasts. When there was a news broadcast, there were more tweets concerning the events
during that time period. When the broadcast was over, the Twitter activity lowered again.
Figure 3-7: The Twitter activity peaks during news broadcasts, indicated by the grey areas.
42
Furthermore, news broadcasts seem to affect the types of tweets sent during the broadcast as
well. Especially during these news broadcasts, it is clearly visible that people posted more
original tweets instead of sharing and retweeting. It might be argued that the news broadcasts
unconsciously incited people to tweet themselves by showing confronting footage of the
events.
Figure 3-8: During news broadcasts indicated by grey areas, people tend to post more
original tweets (OT’s) instead of merely sharing information.
3.3.2.2. Fire in a fast food restaurant in Torhout
Although the dramatic events were shortly mentioned during news broadcasts, they did not
influence the use of Twitter. This might be due to the fact that the fire just got briefly
mentioned, whereas the car pile-up in Zonnebeke occupied almost the entire broadcast and
even led to extra broadcasts. Additionally, the fire started after 20h. A lot of people only heard
about the fire the next day. When looking at the curve, three peaks are visible. However, these
peaks are not caused by news broadcasts (see 3.1.: lapse of Twitter activity).
43
3.3.3. Discussion
The research proved that news websites and news broadcasts have a major impact on the
spread of information, behavior and sensemaking on Twitter during and after fast-burning
emergencies or disasters.
When looking at online news articles, the research concluded that they influence a major part
of the tweets concerning an emergency or disaster. Especially during small-scale situations, it
became clear that the websites of news media have the most influence of the conversations
that are being held. During and after the fire in Torhout, more than 80% of the Tweets
contained a link to an article. More than half of the tweets consisted of a shared article and the
automatic message came with sharing that link. Additionally, 80% of all retweets linked to
online news articles. As a result, online news articles determine the conversations being held
on Twitter concerning small-scale emergency situations. During the large-scale disaster I
analyzed, 43% of the tweets contained a link to news articles. One fifth of all tweets were
merely shared articles and automatic messages that came with them. Additionally, 35% of all
retweets contained links to news articles. News articles thus control conversations on Twitter
concerning a large-scale disaster to a lesser extent.
When looking at the news broadcasts, the research showed that they play a bigger role in
major crisis situations than in smaller ones. First of all, it seems that news broadcasts cause a
peak in the Twitter activity. When there is a news broadcast, there are more tweets concerning
the events during that time period. When the news broadcast is over, the Twitter activity
gradually lowers again. Furthermore, they incite people to form their own messages instead of
sharing or passing on information of others, often leading to more sensemaking than
information or behavior. During and after the small-scale situation I analyzed, those trends
were not visible at all. News broadcasts thus control conversations on Twitter concerning a
small-scale disaster to a lesser extent.
44
4
Conclusions
45
The research showed that news articles are more suitable to spread information and behavior
on Twitter during crisis situation, whereas news broadcasts clearly incite people to react more
emotionally, thus leading to more sensemaking. Furthermore, the research proved that people
tend to spread more news articles during small-scale situations than during large-scale
situations. During those large-scale situations, the conversations are being influenced by news
broadcasts to a bigger extent. As a result, there is way more sensemaking during large-scale
situations than during small-scale situations, while there is significantly more information and
behavior during small-scale situations than during large-scale situations.
It could be argued that media with low media richness are more appropriate to communicate
information and behavior, whereas media with high media richness are necessary to
communicate about sensemaking. Daft & Lengel introduced their Media Richness Theory in
1984. In this theory, they argue that different situations demand for different media to
communicate through, since the specifications of each medium determines the quality of the
communication of a message. Furthermore, they stated that media with low media richness
are more suitable to spread simple, factual messages, whereas media with high media richness
are more suitable to spread more complicated and emotionally loaded messages.
For crisis communication teams, this implies that the scale of the situation determines the way
people communicate on Twitter concerning that situation. When it is a small-scale situation, it
suffices to focus on media with low media richness. That way, they can influence and maybe
even control the conversations on Twitter. However, when it is a large-scale situation, it is not
that simple. During these situations, crisis communication teams will have to spend more time
on media with high media richness, since they incite people to make their own interpretation
of the situation and form their own messages.
46
3
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51
3
List of images &
figures
52
Figure 1-1: The demand for information during crises (Marynissen et al., 2010).
Image 1-2: IBS-analysis executed during a recent bomb threat in Antwerp.
Image 2-1: The car accident resulted in a horrific pile of twisted steel.
Image 2-2: Emergency services blocked the street for a while in order to take care of the
victims.
Figure 3-1: Twitter activity concerning the car pile-up in Zonnebeke.
Figure 3-2: Twitter activity concerning the fire in Torhout.
Figure 3-3: The first peak in the lapse of the Twitter activity is generally caused by people
wanting to spread and share information.
Figure 3-4: Visualization of the ratio between the percentage of IB-tweets and S-tweets
concerning the car pile-up in Zonnebeke.
Figure 3-5: Visualization of the ratio between the percentage of IB-tweets and S-tweets
concerning the fire in Torhout.
Figure 3-6: The percentage of retweets that contain links to news articles reaches its lowest
point between 18h and 20h.
Figure 3-7: The Twitter activity peaks during news broadcasts, indicated by the grey areas.
Figure 3-8: During news broadcasts indicated by grey areas, people tend to post more original
tweets (OT’s) instead of merely sharing information.
53
2
Appendices
Appendix 1: Processed dataset of the car pile-up (Twitter activity)
Appendix 2: Processed dataset of the car pile-up (IBS)
Appendix 3: Processed dataset of the fire (Twitter activity)
Appendix 4: Processed dataset of the fire (IBS)
54
Appendix 1: Processed dataset of the car pile-up (Twitter activity)
Tot.
RT's
Shares
OT's
9u41 - 10u11
67
46
2
19
10u11 - 10u41
127
60
50
17
10u41 - 11u11
277
170
72
35
11u11 - 11u41
424
256
106
69
11u41 - 12u11
401
242
42
117
12u11 - 12u41
380
221
63
96
12u41 - 13u11
305
161
61
83
13u11 - 13u41
294
155
87
52
13u41 - 14u11
145
69
40
36
14u11 - 14u41
155
97
28
30
14u41 - 15u11
123
66
31
26
15u11 - 15u41
85
48
16
21
15u41 - 16u11
94
49
21
24
16u11 - 16u41
70
27
13
30
16u41 - 17u11
75
38
18
19
17u11 - 17u41
62
28
12
22
17u41 - 18u11
92
41
15
36
18u11 - 18u41
58
24
12
22
18u41 - 19u11
107
34
10
63
19u11 - 19u41
143
52
21
70
19u41 - 20u11
57
30
10
17
20u11 - 20u41
58
30
11
17
20u41 - 21u11
61
27
19
15
21u11 - 21u41
41
20
13
8
55
Appendix 2: Processed dataset of the car pile-up (IBS)
I&B
S
9u41 - 10u11
98,51%
1,49%
10u11 - 10u41
96,06%
3,94%
10u41 - 11u11
86,64%
13,16%
11u11 - 11u41
88,92%
11,08%
11u41 - 12u11
75,56%
24,44%
12u11 - 12u41
78,16%
21,84%
12u41 - 13u11
68,85%
31,15%
13u11 - 13u41
81,97%
18,03%
13u41 - 14u11
82,75%
17,25%
14u11 - 14u41
74,84%
25,16%
14u41 - 15u11
72,36%
27,64%
15u11 - 15u41
76,47%
23,53%
15u41 - 16u11
73,41%
26,59%
16u11 - 16u41
64,29%
35,71%
16u41 - 17u11
66,67%
33,33%
17u11 - 17u41
53,23%
46,77%
17u41 - 18u11
35,87%
64,13%
18u11 - 18u41
39,66%
60,34%
18u41 - 19u11
22,43%
77,57%
19u11 - 19u41
23,08%
76,92%
19u41 - 20u11
33,33%
66,67%
20u11 - 20u41
50%
50%
20u41 - 21u11
55,74%
44,26%
21u11 - 21u41
63,42%
36,58%
56
Appendix 3: Processed dataset of the fire (Twitter activity)
20u55 - 21u30
21u30 - 22u
22u - 22u30
22u30 - 23u
23u - 23u30
23u30 - 00u
00u - 00u30
00u30 - 01u
01u - 01u30
01u30 - 02u
02u - 02u30
02u30 - 03u
03u - 03u30
03u30 - 04u
04u - 04u30
04u30 - 05u
05u - 05u30
05u30 - 06u
06u - 06u30
06u30 - 07u
07u - 07u30
07u30 - 08u
08u - 08u30
08u30 - 09u
09u - 09u30
09u30 - 10u
10u - 10u30
10u30 - 11u
11u - 11u30
11u30 - 12u
12u - 12u30
12u30 - 13u
13u - 13u30
13u30 - 14u
14u - 14u30
14u30 - 15u
15u - 15u30
15u30 - 16u
16u - 16u30
16u30 - 17u
17u - 17u30
17u30 - 18u
Tot.
RT's
Shares
OT's
26
34
14
16
39
20
21
5
3
2
0
0
2
2
0
0
0
3
0
1
3
9
3
3
3
0
1
0
0
5
12
2
4
2
6
3
5
20
8
7
5
11
13
16
5
7
4
3
1
2
0
0
0
0
0
0
0
0
0
1
0
0
0
2
1
0
1
0
0
0
0
0
0
0
3
0
0
1
2
4
2
0
3
2
7
12
5
8
34
16
18
3
3
2
0
0
2
2
0
0
0
2
0
1
3
6
1
2
1
0
0
0
0
5
12
2
0
2
5
1
0
14
5
6
2
5
6
6
4
1
1
1
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
1
0
1
0
0
0
0
0
1
0
1
1
3
2
1
1
0
4
57
Appendix 4: Processed dataset of the fire (IBS)
%IB
20u55 - 21u30
21u30 - 22u
22u - 22u30
22u30 - 23u
23u - 23u30
23u30 - 00u
00u - 00u30
00u30 - 01u
01u - 01u30
01u30 - 02u
02u - 02u30
02u30 - 03u
03u - 03u30
03u30 - 04u
04u - 04u30
04u30 - 05u
05u - 05u30
05u30 - 06u
06u - 06u30
06u30 - 07u
07u - 07u30
07u30 - 08u
08u - 08u30
08u30 - 09u
09u - 09u30
09u30 - 10u
10u - 10u30
10u30 - 11u
11u - 11u30
11u30 - 12u
12u - 12u30
12u30 - 13u
13u - 13u30
13u30 - 14u
14u - 14u30
14u30 - 15u
15u - 15u30
15u30 - 16u
16u - 16u30
16u30 - 17u
17u - 17u30
17u30 - 18u
%S
100%
85,30%
78,60%
100%
94,90%
100%
95,20%
100%
100%
100%
0,00%
14,70%
21,40%
0,00%
5,10%
0,00%
4,80%
0,00%
0,00%
0,00%
100%
100%
0,00%
0,00%
100%
0,00%
100%
100%
100%
33,30%
66,70%
66,70%
0,00%
0,00%
0,00%
66,70%
33,30%
33,30%
0%
100,00%
100%
100%
100%
100%
100%
100%
66,70%
100%
90%
100%
85,70%
80%
81,80%
0,00%
0,00%
0,00%
0,00%
0,00%
0,00%
33,30%
0,00%
10,00%
0,00%
14,30%
20,00%
18,20%
58
Tot.
IB
S
26
34
14
16
39
20
21
5
3
2
0
0
2
2
0
0
0
3
0
1
3
9
3
3
3
0
1
0
0
5
12
2
4
2
6
3
5
20
8
7
5
11
26
29
11
16
37
20
20
5
3
2
0
0
2
2
0
0
0
3
0
1
3
9
1
2
2
0
0
0
0
5
12
2
4
2
6
2
5
18
8
6
4
9
0
5
3
0
2
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2
1
1
0
1
0
0
0
0
0
0
0
0
1
0
2
0
1
1
2
PUBLICATIE VAN DE BACHELORPROEF
Ik, ondergetekende Robbert Meulemeester, geef de Hogeschool West-Vlaanderen hierbij de
toelating om het eindwerk met als titel: “An analysis of the influence of news websites and
news broadcasts on the spread of information, behavior and sensemaking on Twitter during
and after fast-burning emergencies and disasters” evenals alle nuttige en praktische
informatie omtrent dit eindwerk op te nemen in een daartoe speciaal opgezette databank
(http://dspace.howest.be) en deze databank via het internet toegankelijk te maken voor alle
mogelijke geïnteresseerden.
Ik geef de hogeschool eveneens de toelating het eindwerk of stukken daaruit te gebruiken
voor afgeleide producten, zoals daar zijn: abstractenverzamelingen en catalogi.
Voor de opname van de samenvatting van mijn eindwerk in de databank en voor het gebruik
van de afgeleide producten vraag ik geen vergoeding aan de Hogeschool West-Vlaanderen.
Mijn toestemming geldt voor de hele beschermingsduur van mijn eindwerk.
Indien ik in de eerste examenkans niet geslaagd ben en het eindwerk moet herschrijven,
vervalt deze toelating automatisch.
Ik verklaar dat mijn werk onuitgegeven is en garandeer aan de Hogeschool West-Vlaanderen
het volle en onbezwaarde genot van de afgestane rechten, tegen welke verstoring, vordering
of ontzetting ook, zowel voor de teksten als voor de documenten die ze illustreren. Ik zal de
Hogeschool West-Vlaanderen vrijwaren tegen alle aanspraken van derden.
Datum:
2 juni 2014
Plaats:
Kortrijk
Handtekening student:
59