A social media and crowdsourcing data mining system for crime prevention during and post-crisis situations

Date14 November 2016
Published date14 November 2016
DOIhttps://doi.org/10.1108/JSIT-06-2016-0039
Pages364-382
AuthorKonstantinos Domdouzis,Babak Akhgar,Simon Andrews,Helen Gibson,Laurence Hirsch
Subject MatterInformation & knowledge management,Information systems,Information & communications technology
A social media and
crowdsourcing data mining
system for crime prevention
during and post-crisis situations
Konstantinos Domdouzis
Department of Computing, Shefeld Hallam University, Shefeld, UK
Babak Akhgar
Centre of Excellence in Terrorism, Resilience, Intelligence and
Organized Crime Research (CENTRIC), Shefeld Hallam University,
Shefeld, UK
Simon Andrews
Department of Computing, Shefeld Hallam University, Shefeld, UK
Helen Gibson
Centre of Excellence in Terrorism, Resilience, Intelligence and
Organized Crime Research (CENTRIC), Shefeld Hallam University,
Shefeld, UK, and
Laurence Hirsch
Department of Computing, Shefeld Hallam University, Shefeld, UK
Abstract
Purpose – A number of crisis situations, such as natural disasters, have affected the planet over
the past decade. The outcomes of such disasters are catastrophic for the infrastructures of modern
societies. Furthermore, after large disasters, societies come face-to-face with important issues, such
as the loss of human lives, people who are missing and the increment of the criminality rate. In
many occasions, they seem unprepared to face such issues. This paper aims to present an
automated social media and crowdsourcing data mining system for the synchronization of the
police and law enforcement agencies for the prevention of criminal activities during and post a
large crisis situation.
Design/methodology/approach – The paper realized qualitative research in the form of a review
of the literature. This review focuses on the necessity of using social media and crowdsourcing data
mining techniques in combination with advanced Web technologies for the purpose of providing
solutions to problems related to criminal activities caused during and after a crisis. The paper
presents the ATHENA crisis management system, which uses a number of data mining
techniques to collect and analyze crisis-related data from social media for the purpose of crime
prevention.
Findings – Conclusions are drawn on the signicance of social media and crowdsourcing data mining
techniques for the resolution of problems related to large crisis situations with emphasis to the
ATHENA system.
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/1328-7265.htm
JSIT
18,4
364
Received 19 June 2016
Revised 19 June 2016
Accepted 22 June 2016
Journalof Systems and
InformationTechnology
Vol.18 No. 4, 2016
pp.364-382
©Emerald Group Publishing Limited
1328-7265
DOI 10.1108/JSIT-06-2016-0039
Originality/value The paper shows how the integrated use of social media and data mining
algorithms can contribute in the resolution of problems that are developed during and after a large
crisis.
Keywords Analysis, Sentiment, Social media, Crisis, Crowdsourcing, ATHENA
Paper type Research paper
1. Introduction
Modern societies are characterized by increased crime rates, which are expressed in a
multi-faceted manner. As societies develop, so does crime. The prevention of any type of
crime is crucial for the maintenance of social stability and the further intellectual and
nancial growth of societies. To ght crime, the causes of criminal behavior must be
identied and understood as well as the ways crime planning is realized. The
advancement of information and communication technologies has enhanced criminal
activities, but at the same time, it provided a powerful tool in the ght against crime.
Specically, the use of such technologies has allowed criminal activities to be realized in
a quicker and more secretive way; however, they also enhanced the ways the law
enforcement agencies (LEAs) monitor and prevent criminal activities. Each type of
crime is characterized by different requirements and can be analyzed under the context
of different circumstances (Kleemans et al., 2012). Especially the issue of criminal
activities during and post a crisis is very sensitive, as the police and LEAs have to face
a number of consequences caused because of the crisis.
For example, after the Haiti earthquake, the crimes rates have increased. This is
because of prisoner escapes during the earthquake and the presence of armed youth
gangs that try to gain control of vulnerable areas. Displaced people who live in tents
around Port-au-Prince are vulnerable to crime, while the danger of rapes for women is
very high. Based on data provided by the Haitian National Police, 5,136 prisoners
escaped, including 700 gang members (Berg, 2010).
Globalization and technological advances have led to the quick and complex
evolution of crime. Cyber-crime is nowadays a well-known term and affects millions of
business and individuals online. The total loss from cyber-crime in years 2000, 2001 and
2002 increased to $265 million, $378 million and $450 million, respectively, while the
total loss from 1997 to 2002 was $2 billion. Examples of cyber-crimes are hacking of
company databases and theft of nancial, product or research and development data
(Nykodym et al., 2005). The terrible 2015 Nepal earthquake was exploited by internet
fraudsters, who sent multiple phishing emails requesting donations for the victims of
the earthquake.
An example of how globalization and technology have enhanced this evolution can
be shown by the way organized crime operates. Organized crime has adopted more
structured models in their operations and uses technology to expand their activities
beyond national levels. The severity of this situation can be proved by the development
by the Obama Administration, of the “Strategy to Combat Transnational Organized
Crime (2011 Strategy)”. The strategy describes the threat of transnational organized
crime networks toward US national security by dening this threat, outlining ve policy
objectives and presenting six priority actions that need to be taken (Bjelopera and
Finklea, 2012). Furthermore, terrorist groups have adopted the use of technology to
carry more sophisticated attacks on their targets. They use also advanced technologies
to ideologically affect large number of people (e.g. use of Web pages and blogs that
365
Data mining
system

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