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Social Media and SMS in the Haiti Earthquake
Julie Dugdale
University of Grenoble 2 / Grenoble
Informatics Lab (LIG)
MJK, 38400 St Martin dʼHères, France
00 33 4 76 51 46 44
Julie.Dugdale@imag.fr
Bartel Van de Walle
Dept. of Information Management,
Tilburg University
5000 LE Tilburg, The Netherlands
0031 13 4662016
bartel@uvt.nl
Corinna Koeppinghoff
Dept. of Information Management,
Tilburg University
5000 LE The Netherlands
0031 13 4662088
corinnakoeppinghoff@googlem
ail.com
ABSTRACT
We describe some first results of an empirical study describing
how social media and SMS were used in coordinating
humanitarian relief after the Haiti Earthquake in January 2010.
Current information systems for crisis management are
increasingly incorporating information obtained from citizens
transmitted via social media and SMS. This information proves
particularly useful at the aggregate level. However it has led to
some problems: information overload and processing difficulties,
variable speed of information delivery, managing volunteer
communities, and the high risk of receiving inaccurate or incorrect
information.
Categories and Subject Descriptors
H.4.2 [Types of Systems]: Decision Support
H.1.1 [Systems and Information Theory]: Value of information
General Terms
Management, Design, Experimentation, Security, Human Factors.
Keywords
Crisis management, humanitarian action, social network, crisis
mapping.
1. INTRODUCTION
In crisis situations assessing and responding to the humanitarian
needs of the affected population is a huge task. In January 2010 an
earthquake of magnitude 7.0 struck Haiti. The capital, Port-au-
Prince, and surrounding communities were severely damaged. An
estimated 200,000 people died,
a similar number were injured, 2.3
million people were displaced, and approximately US$8.1bn of
monetary damage was incurred [1][2]. The response effort
involved hundreds of agencies covering various activity sectors
e.g. emergency shelter, health, telecommunications, and water,
sanitation and hygiene [3]. One of the most immediate problems
was finding and evacuating victims. Search and rescue teams first
perform a local search of the disaster area aided by satellite maps
and other information [4]. However notifications of possible
locations are increasingly being transmitted via social media (e.g.
concerned relatives posting directly to responder agencies sites) or
via SMS.
The paper describes the first results of an empirical study that
included in-depth interviews with crisis managers responsible for
information management and who were involved in the relief
efforts in Haiti. The study focused on how information was
managed and how information technologies were used in
coordinating humanitarian response after the Haiti earthquake.
One area of interest was how social media and SMS are used in
humanitarian actions in crisis situations.
2. INFORMATION SYSTEMS USED IN
HAITI FOR HUMANITARIAN RELIEF
COORDINATION
The Haiti Earthquake disaster gave rise to an unprecedented use
of information systems (IS). In addition humanitarian workers had
to cope with a massive amount of information received through
web portals, platforms, and social networking media, such as SMS
feeds, Facebook, Twitter [5]. The three most prominent IS were
the UN inter-agency OneResponse Website, the SAHANA Free
and Open Source Disaster Management System, and the crowd-
sourcing platform Ushaidi, which focuses largely on social media.
OneResponse is the leading UN collaborative inter-agency
website, developed with help from Microsoft. It aims to enhance
coordination using the ‘cluster approach’ to crisis management,
which groups response activities into 15 sectors or clusters [6].
Information, such as who is doing what and where may be shared
between clusters. However, this website does not explicitly
integrate information sent via SMS or networking sites.
SAHANA contains modules that concentrate on common disaster
coordination problems, e.g. registering missing persons, and
matching aid requests to pledges of help [7][8]. After mapping the
staff of all organizations in Haiti, including their locations, assets
and resources available, work focused on mapping where relief
was most needed. This was done via a module matching requests
for assistance to support provision. Interestingly SAHANA was
later modified to match requests sent from citizens via SMS. To
help process the SMS messages, volunteers located all over the
world were solicited to translate them and put them into the
required SAHANA format. Moreover, SAHANA enabled the use
of geo-referenced data from all kinds of sources.
The Ushahidi Platform is an open source web application for
information collection, visualization and interactive mapping [9].
It allows people to collect and share their own stories using
various mediums such as SMS, Web Forms, Email or Twitter.
Other social media, e.g. Facebook, Twitter, and wikis, were also
used by UN agencies and US aid organizations. The Thomson
Reuters Foundation offered a free Emergency IS, providing users
with practical and reliable information. This system also makes
information available to subscribers via phone text messages [10].
Copyright is held by the author/owner(s).
WWW 2012 Companion, April 16–20, 2012, Lyon, France.
ACM 978-1-4503-1230-1/12/04.
WWW 2012 – SWDM'12 Workshop
April 16–20, 2012, Lyon, France
713
3. ISSUES IN USING SOCIAL MEDIA AND
SMS FOR CRISIS MANAGEMENT
Generally, the employed IS proved to be very helpful after the
earthquake, mainly because they were easy to use by a diverse
group of actors and because of their accessibility. However one
aspect that makes the Haiti rescue response unique is the use of
social media and SMS by citizens requesting help. As one Search
and Rescue Team Leader said “… one of the things that happened
in Haiti and that we had not seen before was that we had a lot of
reports come in about people that had been trapped in the rubble
through media….. For the first time you could say that a lot of
people were sending SMS….”. Although this provided additional
information, the time taken for the rescuers to receive such
information varied enormously: “The path of how those SMS got
to us was often very different. Some of them went a long way:
someone in Haiti SMS-ed their family in the US, the family in the
US talked to the State Senator of the state they live in, the Senator
talked to the State department, the State department contacted the
US embassy in Haiti, the embassy in Haiti gave it to the SAR
people from the US and they shared it with us. It’s a long
information trip.” Furthermore this additional information also
brought the inevitable problem of information overload: “..how do
we deal with this overflow of data that’s coming in now through
this new media, such as Twitter and Facebook. How do you deal
with all of that information?”. A solution used by some teams was
to use a globally dispersed, virtual community of humanitarian
volunteers. However, whilst this solved some problems it proved
difficult to manage these communities. An additional problem
was that the value of the information to the rescuers at the street
level was mainly useless, but the aggregation of information from
various sources proved very helpful. The following quote shows
this and also how the emotional state of the citizens affects texting
behavior: “…when it got down to the street level, the information
was not very accurate…up to 90% of the reports of people
trapped in the rubble were not correct. The same way, I heard
from the Marines that most of the information they were getting
about looting, etc. usually was not very correct. When you looked
at it from an area perspective, the information became usable.
When you aggregated the information about the people being
trapped in the rubble and you looked where are the largest
number of reports of people came from, that would show you
where the concentration of collapsed houses was. …people will
report things based on their emotional state. When you have been
through a very traumatic experience like an earthquake, to you
things may seem devastating even though they may not be. You
may be reporting 100% correctly based on your emotional state
but it may not give you an accurate view of what the situation is
on the ground. I’ve heard from other places that the social media
reports are also not very accurate, because people will also try to
use them to try to get help to their areas. But even though 90%
may not be correct at the street level, 80% may be correct at the
area level, when you aggregate the information. So we shouldn’t
dismiss them. We should think about what are we using it for.”
4. CONCLUSIONS
The increasing use of social media and SMS in rescue response
and crisis management raises interesting issues. Information from
citizens via social media and SMS proved useful in Haiti,
particularly when it was aggregated at an area level. However
there were problems: information overload; questionable speed of
information delivery; difficulties of processing information in a
non-standard format from different sources and in various
languages; the complexity of managing volunteer communities;
and the very limited value of using information at the street level.
One of the most marked aspects of rescue response in Haiti was
the emergence of a global humanitarian volunteer community. In
future it is important to harness the potential of this community, to
improve collaboration mechanisms and to identify what is the best
way to use the provided information.
5. ACKNOWLEDGMENTS
We wish to thank members of the USAR (Urban Search and
Rescue) teams, UNDAC (UN Disaster Assessment and
Coordination) and OCHA (Office for the Coordination of
Humanitarian Affairs) for their participation in the study and
whose quotes we have used.
6. REFERENCES
[1] Carvallo, E., Powell, A., and Becerra, O. 2010. Estimating
the direct economic damages of the Earthquake in Haiti. The
Economic Journal. 120, 546, F298-F312.
[2] OCHA Report. 2012. Haiti: Two years after the devastating
earthquake. http://www.unocha.org/top-stories/all-
stories/haiti-two-years-after-devastating-earthquake
Retrieved Jan 20, 2012.
[3] Van de Walle, B. and M. Turoff (2008), “Decision Support
for Emergency Situations”, International Journal of
Information Systems and e-Business Management 6:3
(2008), 295-316.
[4] Van de Walle, B., G. Van Den Eede and W. Muhren,
“Humanitarian Information Management and Systems”,
Lecture Notes Computer Science 5424 (Eds. J. Lofler and M.
Klahn) (2009), pp. 12-21.
[5] US Department of State. 2010. Haiti Earthquake: Breaking
New Ground in the Humanitarian Information Landscape,
White Paper, Humanitarian Information Unit, July 2010,
http://www.odihpn.org/report.asp?id=3135 Retrieved Aug 6,
2011
[6] OCHA OneResponse. 2012. OCHA IM Toolkit. AK Peters
Ltd., MA http://oneresponse.info/resources/imtoolbox/
Retrieved Jan 20, 2012.
[7] SAHANA. 2010, United Nations APCICT-ESCAP: ICT For
Disaster Risk Reduction – ICTD Case Study 2, May 2010,
http://www.unapcict.org/ecohub/ict-for-disaster-risk-
reduction-1 Retrieved Aug 6, 2011
[8] Currion, P., C. de Silva and B. Van de Walle (2007), “Open
Source Software for Disaster Management”,
Communications of the ACM 50:3, pp. 61 – 65.
[9] Ushahidi. 2011. Platforms and Crowdmap.
http://www.ushahidi.com/ Retreived Jan 20, 2012.
[10] Reuters. 2010, Haiti wants more information on foreign aid,
http://www.reuters.com/article/2010/03/03/us-quake-haiti-
eu-idUSTRE6225UO20100303 Retrieved Aug 6, 2011
WWW 2012 – SWDM'12 Workshop
April 16–20, 2012, Lyon, France
714
