SlideShare uma empresa Scribd logo
1 de 12
Baixar para ler offline
Online Social Networks and Terrorism 2.0 in
Developing Countries
Fredrick Romanus Ishengoma
College of Informatics and Virtual Education, The University of Dodoma, Dodoma, Tanzania.
ishengomaf@gmail.com
Abstract
The advancement in technology has brought a new era in terrorism where Online Social Networks (OSNs)
have become a major platform of communication with wide range of usage from message channeling to
propaganda and recruitment of new followers in terrorist groups. Meanwhile, during the terrorist attacks
people use OSNs for information exchange, mobilizing and uniting and raising money for the victims. This
paper critically analyses the specific usage of OSNs in the times of terrorisms attacks in developing
countries. We crawled and used Twitter’s data during Westgate shopping mall terrorist attack in Nairobi,
Kenya. We then analyzed the number of tweets, geo-location of tweets, demographics of the users and
whether users in developing countries tend to tweet, retweet or reply during the event of a terrorist attack.
We define new metrics (reach and impression of the tweet) and present the models for calculating them.
The study findings show that, users from developing countries tend to tweet more at the first and critical
times of the terrorist occurrence. Moreover, large number of tweets originated from the attacked country
(Kenya) with 73% from men and 23% from women where original posts had a most number of tweets
followed by replies and retweets.
Keywords: Developing Countries, Online Social Networks, Terrorism 2.0, Twitter and Westgate.
I. Introduction
Online Social Networks (OSNs) example Twitter, Facebook, and YouTube have emerged as
major means of communication for people in sharing and exchanging information on a wide
variety of real-world events. As technology and Internet advances in developing countries, users
from developing regions are also increasing in using OSNs (Reda, 2012). Numerous studies have
shown that users from developing countries are spending a significant amount of time in OSNs
(Karel 2007; Reda 2011). Another OSNs study (Pew Research Center, 2010) showed many
people in developing countries do not go online, however when they have the opportunity to go
online, they tend to use online social networking sites. For example, one-in-five Kenyans (19%)
participate in online social networking, while just 5% use the Internet but do not participate.
Of the users that go online in developing countries, the demographics have shown a double-digit
difference in gender gap where more men tend to go online compared to women (Pew Research
Center, 2010; Intel, 2013). A recently study by Intel showed that on average, 23% fewer women
than men are online in developing countries (Intel, 2013).
While the OSNs users can use the technology positively for communication and information
exchange, yet the same technology can also be used negatively as a tool for terrorism 2.0.
Terrorism 2.0 is the use of web 2.0 applications and semantic technologies in assisting or
performing terrorist acts. With web 2.0, terrorist are able to connect them using social networks
for sharing information, disseminate propaganda, recruiting new members and even planning an
attack. For example, Al-Shabaab, a terrorist group based in Somalia, used Twitter during a
Westgate terrorist attack in Nairobi to disseminate information and claiming responsibility of the
attack.
Meanwhile, during terrorist attacks people have been using these OSNs to break the news,
provide information with rich media content and uniting people for providing help and
fundraising for the victims. For example, during the Westgate attack Twitter was used to
mobilize the country for blood donation, money donation as well as keeping the peace. People
used the hashtag #WeAreOne for uniting the country through updates and insights and raising
money for the victims.
The aim of this paper is to analyze how OSNs is being used during the event of a terrorist attacks
in developing countries along. We perform activity analysis of Twitter after the Westgate attack
in Nairobi. Moreover, we present the OSNs challenges and opportunities in relation to terrorism
2.0. The rest of the paper is organized as follows: We start by providing related work in section
2. Section 3 is dedicated to the background of terrorism 2.0 and OSNs. Section 4 discuses
Twitter in the era of Terrorism 2.0 with subsections on how people use Twitter and Twitter as a
terrorist assistance tool. Data collection is discussed in Section 5. Section 6 discuses and analyses
the findings of the study. We conclude in Section 7.
II. Related Work
In this section, we provide an overview of various studies that are related to our research work.
A number of studies (Murthy, 2010; Mendoza, 2010, Stollberg, 2012; Nagar, 2012; Hossmann,
2012) have focused their work on the usage of OSNs during disasters like floods and earthquakes
and in facilitating event detection and responses to emergency situations (Becker, Naaman, and
Gravano 2011; Li, Sun, and Datta 2012; Li et al. 2012; Weng et al. 2011).
Weimann (Weimann, 2011) describes how the advances of technology has changed terrorist
online communication from one-directional to bi-directional with interactive capabilities like
chat-rooms, online social networking sites, video-sharing sites. (Veerasamy, 2012) represented
the functions and methods that terrorists have come to rely on through the Information and
Communication Technology (ICT) infrastructure. The discussion sheds light on the technical and
practical role that ICT infrastructure plays in the assistance of terrorism.
(Gupta, 2011) attempt to characterize and extract patterns of activity of users on Twitter during a
crisis based on the Mumbai terrorist attack. The study attempted to characterize and extract
patterns of activity of users on Twitter during a terrorist situation. Another close related work is
by Oh and Agrawal, (Oh, 2011). They analyzed the Twitter stream during the 2008 Mumbai
terrorist attacks. The study applied social awareness theory to show how information available
on OSNs during the attacks aided the terrorists’ decision making.
While some of the studies have the similar objectives with our study, our study remains unique
as it focuses on a OSNs usage during terrorists attack in a developing country context.
III. Terrorism 2.0 and Online Social Networks
In this section we will provide an introductory overview of Terrorism 2.0 and Online Social
Networks (OSNs) and how they are related.
A. Terrorism 2.0
As Information and Communication Technologies (ICTs) advances and transform how we live,
it also changes the terrorism era. Advances in IT has brought a new era of Terrorism 2.0 where
terrorist now make use of high advancement of IT to accomplish their goals. OSNs have now
been used by terrorists for communication, recruiting new members, transmitting training videos
and materials and propaganda.
For example, one terrorist website provide details on how to make Improvised Explosive
Devices (IEDs), a bomb that can be made from locally available materials. Other terrorist
websites have been distributing materials (tutorials and books) online on how to make poisons,
bombs and conduct a terrorist attack. Some of the popular terrorist books that circulate online are
The Mujahideen Poisons Handbook and The Anarchist’s Cookbook.
B. Online Social Networks
Online Social Networking Sites (OSNs) are kind of social media that gives ability online user to
make a profile with his information and enable users to share and exchange messages and
multimedia content (Boyd & Ellison, 2008). Some examples of popular social networks include
Facebook, Twitter, YouTube and Flickr. They depend on peer-to-peer (P2P) networks that are
cooperative, distributed, and community driven. Within the OSNs users can create groups for
people with common interest to share information and communicate privately.
Recently, terrorists have changed from its traditional ways of communicating to adapt the use of
OSNs as their platform of communication. OSNs has opened a new way to terrorists enabling
them to communicate easily and more secure, disseminate information, propaganda and training
materials, organize attacks, recruiting new members and to seek sympathy to the public for their
actions worldwide.
IV. Twitter in the Era of Terrorism 2.0
With registered users more than 500 million worldwide as of October 2013, Twitter is one of the
most popular online social networks available. Twitter offers exchange of short messages called
Tweets of up to 140 characters long between its users. Hashtags are words prefixed with ‘#’
used by Twitter users to describe a subject (e.g. #BreakingNews). Common practice of
responding to a tweet has evolved into well-defined mark-up culture: RT stands for Retweet. A
retweet is a message from one user that is forwarded by a second user. The retweet mechanism
empowers users to spread information of their choice beyond the reach of the original tweet’s
followers. A message from one Twitter user that is a response to Twitter user’s message is called
a Reply. Being a follower on Twitter means that the user receives all the tweets from those the
user follows. We opted to use Twitter as our choice of OSN for this study due to its availability
of data.
A. How people use Twitter?
Studies have shown that people use Twitter for different purposes (Java, 2007; Ramage, 2010;
Naaman, 2010) studied the aims of 94,000 Twitter users with more than 1.3 million tweets and
concluded that users make use of Twitter in the following major areas:
(i) Chatting. Most Twitter users are for discussion of day-to-day activities.
(ii) Conversations. Some of the Twitter users engage in the conversation using replies
mechanism.
(iii) Information exchange/Sharing. Twitter users share and exchange information through
Twitter posts contains URLs.
(iv) News. Reporting and commenting on breaking news and latest news is another type of
people’s usage in Twitter.
B. Twitter as a Terrorist Assistance Tool
OSN is a suitable platform for terrorists because of its easy access, little control from the
governments, worldwide audience, anonymity (via fake profiles), fast flow of information, cheap
development of OSN websites and multimedia platform (the capability to combine text, graphics,
audio, video and downloading). With the current highly development of Information and
Communication Technologies (ICTs) terrorist uses OSN for the following purposes:
(i) Information exchange. Terrorist use OSN to communicate with worldwide audience than
it was a decade before. Terrorists have become sophisticated in using
anonymous/secret communications using encryption, steganography and anonymity
softwares. Example, Al-Qaeda members have been using encryption softwares
“Mujahedeen Secrets 1” and “Mujahedeen Secrets 2” to encrypt and secure their
email communications.
(ii) Recruiting and Training. A report by the institute of homeland security of the George
Washington University (Homeland Security Institute, 2009) relays that the Internet
has become crucial instrument in the hands of terrorists to spread their messages and
recruit new supporters. Nowadays terrorists’ recruitment and training can be
successfully offered via OSNs easily and anonymously unlike before, which required
the physical meetings of trainees and trainers. Recruits are passing through a series of
tests in password protected websites and restricted chat rooms before accepted and
joining the terrorist group (Gerwehr, 2006). Tactics used includes the integration of
terrorist acts in cartoons and music videos to attract the minors into terrorism. Also,
video games that involve the acts of terrorism like mass suicide attack.
(iii) Planning attacks. OSNs are used by terrorists to plan an attack due to its secure
communication and fast message channeling.
(iv) Fundraising. Through wire transfer and email address the groups are able to conduct a
fundraising in OSNs.
(v) Cyber-attack. Cyber-attack refers to the use of computer networking tools to attack other
computer networks or national communications systems like government operations,
transportation, and energy.
(vi) Propaganda. Though these OSN have played a great role in the society, at the same time
the terrorists is using them for their propaganda dissemination. These propaganda
deals with delivering ideological, clarifications, explanations or campaign of terrorist
actions. These can involve messages, demonstrations, magazines, audio and video
footage of violent acts.
On 16 March 2013, the propaganda arm of al-Qaeda, the Andalus Foundation, created a twitter
account (@Andalus_Media). The account has gained more than 14,500 followers while
following 7 people inclusing the Somali terrorist group Al Shaabab. Al-Shabaab (Kimunguyi
(2010), Ibrahim (2010)) also known as Harakat al-Shabaab al-Mujahideen (HSM) started their
Twitter account in English as HSM Office on December 2011 using the Twitter handle
‘@HSMPress’ (https://twitter.com/#!/HSMPress). HSMPress is the press branch of Al-Shabaab
(HSM). Since then they have been using Twitter to exaggerate their military accomplishments.
Al-Shabaab has been in battle with Kenya (due to presence of Kenyan Army in Somalia) that has
led to Westgate attack in September 2013 Nairobi. The terrorist group’s Twitter account has
been repetitive suspended by Twitter due to violation of terms of service. Twitter’s terms of
service state that users “may not publish or post direct, specific threats of violence against
others.” However each time their account is suspended, they create new accounts with some
slight variations on the same name such as @HSMPRESS1, @HSM_PressOffice,
@HSM_PROffice and @HSM_PR.
Figure. 1. Cover of Al-Shabaab’s English Twitter page as of 13 August 2013.
Figure. 2. Example of Al-Shabaab’s Tweet during the Westgate attack.
V. Data
Our case study is the terrorist attack of Westgate shopping mall in Nairobi, Kenya on 21st
September 2013. The attack lasted until 24th September resulting in at least 72 deaths and over
200 wounded people (Raidió Teilifís Éireann, 2013). The Islamist group Al-Shabaab claimed
accountability for the terrorist attack.
We used Twitter search API during the Westgate attack period when the text string ‘#Westgate’
was most active and Topsy (Topys, 2013), a certified Twitter partner that maintains the world’s
largest index of tweets, numbering in hundreds of billions, dating back to May 2008. We crawled
the data of the popular Twiter #hashtags that was used during the Westgate attack namely;
#Westgate. The #Westgate hashtag was used in tweeting by both the terrorists and the civilians.
We analyzed data between 21st and 27th to obtain the clear picture of the patterns. These data
are analyzed to explore the following metrics:
(i) Number of tweets during the terrorist attack.
(ii) Whether users tend to tweet, retweet or reply in Twitter during the event of
Westgate terrorist attack.
(iii) What countries had the highest frequency of tweets during the Westgate terrorist
attack.
(iv) What are the demographics of the Twitter users during the Westgate terrorist
attack and
(v) What were the reachness and impressions of the tweets during the Westgate
terrorist attack?
VI. Findings and Discussion
In this section we present our findings of the study and discussion. We begin by examining the
number of tweets that were sent during the #Westgate attack. While there were many other
hashtags used to discuss the terrorist attack in Twitter posts (like #Nairobi, #Kenya, #Terrorist),
we chose the #Westgate hashtag since it was the most relevant one and standard one. We
considered the number of tweets that uses only the hashtag ‘Westgate’.
Figure. 3. Number of tweets during the #Westgate attack.
Figure 3 shows the number of tweets tweeted using #Westgate hashtag during the Westgate
attack period between 21st September. The number of tweets is observed to be high during the
first hours of the terrorist attack and when the terrorist attack is in its peak. This is due to the
Twitter’s real time nature i.e. the behaviour of Twitter users to post about events as they are
happening. The tweets are observed to decrease as the terrorist attack ends.
Figure 4. Geographical distribution of tweets during the #Westgate attack.
Figure 4 shows the geographical distribution of tweets during the Westgate attack. From the
figure it is observed that most of the tweets came from the developing countries. Kenya being the
countries tweeted mostly about the attack, this could be because it is the attacked country. Also,
a significant number of tweets is shown to have originated from US and UK.
We then analyzed the Twitter data to find out, how many tweets were original posts, retweets or
replies using the keyword #Westgate.
Figure 5. Sharing of tweets (original, retweets and replies) during the #Westgate attack.
Figure 5 shows the sharing of Twitter posts during the Westgate attack. From the figure it is
observed that most of the tweets during the attack were original posts (65%), followed by
retweets (27%) and replies (8%).
In figure 6 we analyzed the reach and impression of #Westgate tweets during the terrorist attack.
We define reach, as the number of unique followers that a user has that is, the unique people who
a tweet could potentially get to. We define impression as the number of times a user posts that is,
how many times followers would see these posts. Let N be the number of followers a Twitter
user has and t the number of times a tweet is tweeted. Reach is given by N whereby Nt gives
impression. For example, if a Twitter user has 300 followers In figure 6 we analysed the reach
and impression of #Westgate tweets during the terrorist attack. We define reach, as the number
of unique followers that a user has that is, the unique people who a tweet could potentially get to.
We define impression as the number of times a user posts that is, how many times followers
would see these posts. Let N be the number of followers a Twitter user has and t the number of
times a tweet is tweeted. Reach is given by N whereby Nt gives impression. For example, if a
Twitter user has 300 followers and tweet 3 times then tweet’s reach is 300 and tweet’s
impression is 900 (since 300 followers saw the tweet thrice).
Figure 6. Reach and Impression of tweets during the #Westgate attack.
We then analyzed the demography of the Twitter posts during the #Westgate attack. In Figure 7
we could see the percentage of male and female who tweeted about the terrorist attack using
#Westgate hashtag. Males are observed to tweet more than females. 73% of the #Westgate
tweets are observed to be from males while 27% of the #Westgate tweets are from females. This
could be due to the gender gap in developing countries where according to International
Telecommunication Union (ITU, 2013), 16% fewer women than men use the Internet in
developing countries.
Figure 7. Demography of Twitter posts during the #Westgate attack.
VII. Conclusion
In this paper, we analyzed the usage of Online Social Networks (OSNs) in the event of a terrorist
attack with a case study of a Westgate shopping mall attack in Nairobi, Kenya. We used different
metrics like number of tweets, whether users in developing countries tended to tweet, retweet or
reply, demographics, geo-location and we defined new metrics (reach and impression of the
tweet) and presented their models. While the developing countries are faced by many limitations
in using OSNs such as unreliable power and poor Internet connection, still the study finding
challenges the traditional media of reporting during disasters like terrorists attacks. We
recommend centers globally to make full use of the OSNs for crisis communication in order to
save more lives during such.
References
i. Aditi Gupta, Ponnurangam Kumaraguru, Twitter Explodes with Activity in Mumbai
Blasts! A Lifeline or an Unmonitored Daemon in the Lurking? PSOSM '12 Proceedings
of the 1st Workshop on Privacy and Security in Online Social Media, 2012.
ii. Azarias Reda, Sam Shah, Mitur Tiwali, Anita Lillie, Brian Noble, Social Networking in
Developing Regions, Fifth International Conference on Information and Communication
Technologies and Development (ICTD 2012), 2012.
iii. Azarias Reda, Edward Cutrell, and Brian Noble, Towards Improved Web Acceleration:
Leveraging the Personal Web. In Pro- ceedings of the 5th ACM Workshop on Networked
Systems for Developing Regions (NSDR), pages 57 - 62, Bethesda, Maryland, USA,
June 2011.
iv. Beate Stollberg, Tom de Groeve, The Use of Social Media within the Global Disaster
Alert and Coordination System (GDACS), WWW– SWDM'12 Workshop April 16–20,
2012, Lyon, France, 2012.
v. Becker, H.; Naaman, M.; and Gravano, L, Beyond Trending Topics: Real-world Event
Identification on Twitter. In Proc. of WSM, 2011.
vi. Dhiraj Murthy & Scott A. Longwell, Twitter and Disasters: The uses of Twitter during
the 2010 Pakistan floods, May 2012.
vii. Gabriel Weimann, Lone Wolves in Cyberspace, Journal of Terrorism Research, Volume
3, Issue 2, 2012.
viii. Gabriel Wimann, Al Qaeda Has Sent You A Friend Request: Terrorists Using Online
Social Networking, Israeli Communication Association, 2011.
ix. Homeland Security Institute (2009), The Internet as a Terrorist Tool for Recruitment and
Radicalization of Youth, US Department of Homeland Security, Science and Technology
Directorate.
x. Ibrahim, M. (2010), Somalia and Global Terrorism: A Growing Connection? Journal of
Contemporary African studies, Volume 28:3, pp.283-295.
xi. Java, A., X. Song, T. Finin, and B. Tseng, Why We Twitter: Understanding
Microblogging Usage and Communities, In WebKDD/SNA-KDD ’07: Proceedings of
the 9th WebKDD and 1st SNA-KDD 2007 Workshop on Web Mining and Social
Network Analysis, New York, NY, USA, pp. 56–65. ACM, 2007.
xii. Karel Matthee, Gregory Mweemba, Adrian Pais, Gertjan van Stam, and Marijn Rijken,
Bringing Internet Connectivity to Rural Zambia Using a Collaborative Approach, In
Proceedings of the 2nd ACM International Conference on Information and
Communication Technologies and Development (ICTD), pages 47–58, Bangalore, India,
December 2007.
xiii. Li, C.; Sun, A.; and Datta, A. Twevent, Segment-based Event De tection from Tweets. In
Proc. of CIKM, 2012.
xiv. Li, R.; Lei, K. H.; Khadiwala, R.; and Chang, K. C.-C. TEDAS: A Twitter-based Event
Detection and Analysis System. In Proc. of ICDE, 2012.
xv. Naaman, M., J. Boase, and C.-H. Lai, Is it Really about Me?: Message Content in Social
Awareness Streams, In Proceedings of the 2010 ACM Conference on Computer
Supported Cooperative Work, CSCW ’10, New York, NY, USA, pp. 189–192. ACM,
2010.
xvi. Marcelo Mendoza, Barbara Poblete, and Carlos Castillo. Twitter Under Crisis: Can We
Trust What We RT? In 1st Workshop on Social Media Analytics (SOMA ’10). ACM
Press, July 2010.
xvii. Onook Oh, Manish Agrawal, and H. Raghav Rao. Information Control and Terrorism:
Tracking the Mumbai Terrorist Attack through Twitter. Information Systems Frontiers,
13(1):33–43, 2011.
xviii. Patrick Kimunguyi (2010), Terrorism and Counter Terrorism in East Africa, Global
Terrorism Centre, 2010.
xix. Pew Research Center. Global Publics Embrace Social Networking. Pew Global Attitudes
Project, 2010.
xx. Raidió Teilifís Éireann, Kenyan Military Frees Most Hostages at Mall, 23 September
2013. Retrieved 24 September 2013.
xxi. Ramage, D., S. Dumais, and D. Liebling, Characterizing Microblogs with Topic Models.
In ICWSM, 2010.
xxii. Seema Nagar, Aaditeshwar Seth, Anupam Joshi, Characterization of Social Media
Response to Natural Disasters), WWW– SWDM'12 Workshop April 16–20, 2012, Lyon,
France, 2012.
xxiii. Scott Gerwehr and Sarah Daly (2006), Al-Qaida: Terrorist Selection and Recruitment, in
The McGraw-Hill Homeland Security Handbook, David Kamien, ed. (New York,
McGraw-Hill), pp. 83.
xxiv. Theus Hossmann, Paolo Carta, Dominik Schatzmann, and Franck Legendre, Per
Gunningberg, Christian Rohner, Twitter in Disaster Mode: Security Architecture,
Proceedings of the Special Workshop on Internet and Disasters. Tokyo, Japan: ACM,
2011.
xxv. Weng, J.; Yao, Y.; Leonardi, E.; and Lee, F. Event Detection in Twitter. In Proc. of
WSM, 2011

Mais conteúdo relacionado

Mais procurados

Fusing text and image for event
Fusing text and image for eventFusing text and image for event
Fusing text and image for eventijma
 
Completed Portfolio for Linkedin
Completed Portfolio for LinkedinCompleted Portfolio for Linkedin
Completed Portfolio for LinkedinMatthew Darrington
 
Filter bubble and information behaviour, ISIC 2018, keynote speech
Filter bubble and information behaviour, ISIC 2018, keynote speechFilter bubble and information behaviour, ISIC 2018, keynote speech
Filter bubble and information behaviour, ISIC 2018, keynote speechSabina Cisek
 
IJSRED-V2I3P23
IJSRED-V2I3P23IJSRED-V2I3P23
IJSRED-V2I3P23IJSRED
 
Online privacy and the librarian
Online privacy and the librarianOnline privacy and the librarian
Online privacy and the librarianabeldridge
 
Using Twitter Data to Provide Qualitative Insights into Infectious Disease Ou...
Using Twitter Data to Provide Qualitative Insights into Infectious Disease Ou...Using Twitter Data to Provide Qualitative Insights into Infectious Disease Ou...
Using Twitter Data to Provide Qualitative Insights into Infectious Disease Ou...Dr Wasim Ahmed
 
Information 2.0 and beyond where are we going
Information 2.0 and beyond  where are we goingInformation 2.0 and beyond  where are we going
Information 2.0 and beyond where are we goingHero Wa
 
Can Artificial Intelligence Predict The Spread Of Online Hate Speech?
Can Artificial Intelligence Predict The Spread Of Online Hate Speech?Can Artificial Intelligence Predict The Spread Of Online Hate Speech?
Can Artificial Intelligence Predict The Spread Of Online Hate Speech?Bernard Marr
 
lis 3201 Final presentation
lis 3201 Final presentationlis 3201 Final presentation
lis 3201 Final presentationMonte VanDyke
 
How india muslims are being demonised through whats app groups (a critical study
How india muslims are being demonised through whats app groups (a critical studyHow india muslims are being demonised through whats app groups (a critical study
How india muslims are being demonised through whats app groups (a critical studyZahidManiyar
 
War on the Web The various frames of the Libyan conflict in French online news
War on the Web The various frames of the Libyan conflict in French online news War on the Web The various frames of the Libyan conflict in French online news
War on the Web The various frames of the Libyan conflict in French online news smyrnaios
 
051115_Writing Sample_Kaorop
051115_Writing Sample_Kaorop051115_Writing Sample_Kaorop
051115_Writing Sample_KaoropMukkamol Kaorop
 
A BRIEF SURVEY OF MOBILE FORENSICS ANALYSIS ON SOCIAL NETWORKING APPLICATION
A BRIEF SURVEY OF MOBILE FORENSICS ANALYSIS ON SOCIAL NETWORKING APPLICATIONA BRIEF SURVEY OF MOBILE FORENSICS ANALYSIS ON SOCIAL NETWORKING APPLICATION
A BRIEF SURVEY OF MOBILE FORENSICS ANALYSIS ON SOCIAL NETWORKING APPLICATIONNana Kwame(Emeritus) Gyamfi
 
Journalism fake news disinformation
Journalism fake news disinformationJournalism fake news disinformation
Journalism fake news disinformationVittorio Pasteris
 

Mais procurados (20)

The RuNet generation
The RuNet generationThe RuNet generation
The RuNet generation
 
Fusing text and image for event
Fusing text and image for eventFusing text and image for event
Fusing text and image for event
 
Completed Portfolio for Linkedin
Completed Portfolio for LinkedinCompleted Portfolio for Linkedin
Completed Portfolio for Linkedin
 
Filter bubble and information behaviour, ISIC 2018, keynote speech
Filter bubble and information behaviour, ISIC 2018, keynote speechFilter bubble and information behaviour, ISIC 2018, keynote speech
Filter bubble and information behaviour, ISIC 2018, keynote speech
 
IJSRED-V2I3P23
IJSRED-V2I3P23IJSRED-V2I3P23
IJSRED-V2I3P23
 
Online privacy and the librarian
Online privacy and the librarianOnline privacy and the librarian
Online privacy and the librarian
 
Using Twitter Data to Provide Qualitative Insights into Infectious Disease Ou...
Using Twitter Data to Provide Qualitative Insights into Infectious Disease Ou...Using Twitter Data to Provide Qualitative Insights into Infectious Disease Ou...
Using Twitter Data to Provide Qualitative Insights into Infectious Disease Ou...
 
Information 2.0 and Beyond: Where are we, where are we going?
Information 2.0 and Beyond: Where are we, where are we going?Information 2.0 and Beyond: Where are we, where are we going?
Information 2.0 and Beyond: Where are we, where are we going?
 
Information 2.0 and beyond where are we going
Information 2.0 and beyond  where are we goingInformation 2.0 and beyond  where are we going
Information 2.0 and beyond where are we going
 
Can Artificial Intelligence Predict The Spread Of Online Hate Speech?
Can Artificial Intelligence Predict The Spread Of Online Hate Speech?Can Artificial Intelligence Predict The Spread Of Online Hate Speech?
Can Artificial Intelligence Predict The Spread Of Online Hate Speech?
 
lis 3201 Final presentation
lis 3201 Final presentationlis 3201 Final presentation
lis 3201 Final presentation
 
Go Mobile
Go MobileGo Mobile
Go Mobile
 
How india muslims are being demonised through whats app groups (a critical study
How india muslims are being demonised through whats app groups (a critical studyHow india muslims are being demonised through whats app groups (a critical study
How india muslims are being demonised through whats app groups (a critical study
 
Duty identity-credibility
Duty identity-credibilityDuty identity-credibility
Duty identity-credibility
 
War on the Web The various frames of the Libyan conflict in French online news
War on the Web The various frames of the Libyan conflict in French online news War on the Web The various frames of the Libyan conflict in French online news
War on the Web The various frames of the Libyan conflict in French online news
 
051115_Writing Sample_Kaorop
051115_Writing Sample_Kaorop051115_Writing Sample_Kaorop
051115_Writing Sample_Kaorop
 
Information on the go
Information on the goInformation on the go
Information on the go
 
A BRIEF SURVEY OF MOBILE FORENSICS ANALYSIS ON SOCIAL NETWORKING APPLICATION
A BRIEF SURVEY OF MOBILE FORENSICS ANALYSIS ON SOCIAL NETWORKING APPLICATIONA BRIEF SURVEY OF MOBILE FORENSICS ANALYSIS ON SOCIAL NETWORKING APPLICATION
A BRIEF SURVEY OF MOBILE FORENSICS ANALYSIS ON SOCIAL NETWORKING APPLICATION
 
Connecting and protecting
Connecting and protectingConnecting and protecting
Connecting and protecting
 
Journalism fake news disinformation
Journalism fake news disinformationJournalism fake news disinformation
Journalism fake news disinformation
 

Destaque

Chapter 13
Chapter 13Chapter 13
Chapter 13detjen
 
Arte a medio dibujar
Arte a medio dibujarArte a medio dibujar
Arte a medio dibujarmaugepe
 
Cyber safety, technology and the church
Cyber safety, technology and the churchCyber safety, technology and the church
Cyber safety, technology and the churchPaul OBriant
 
Adam Mtaho & Fredrick Ishengoma - Factors Affecting QoS in Tanzania Cellular ...
Adam Mtaho & Fredrick Ishengoma - Factors Affecting QoS in Tanzania Cellular ...Adam Mtaho & Fredrick Ishengoma - Factors Affecting QoS in Tanzania Cellular ...
Adam Mtaho & Fredrick Ishengoma - Factors Affecting QoS in Tanzania Cellular ...Fredrick Ishengoma
 
Luxembourg Blockchain Meetup 13 July 2016 - Bertolo
Luxembourg Blockchain Meetup 13 July 2016 - BertoloLuxembourg Blockchain Meetup 13 July 2016 - Bertolo
Luxembourg Blockchain Meetup 13 July 2016 - BertoloStefano Bertolo
 
Chapter 6
Chapter 6Chapter 6
Chapter 6detjen
 
Collaborative archietyped for ipv4
Collaborative archietyped for ipv4Collaborative archietyped for ipv4
Collaborative archietyped for ipv4Fredrick Ishengoma
 
Deploying the producer consumer problem using homogeneous modalities
Deploying the producer consumer problem using homogeneous modalitiesDeploying the producer consumer problem using homogeneous modalities
Deploying the producer consumer problem using homogeneous modalitiesFredrick Ishengoma
 
Chapter 4
Chapter 4Chapter 4
Chapter 4detjen
 
Plenary Session - Technology and the Church
Plenary Session - Technology and the ChurchPlenary Session - Technology and the Church
Plenary Session - Technology and the ChurchPaul OBriant
 
Dakotas Parent Meeting Presentation
Dakotas Parent Meeting PresentationDakotas Parent Meeting Presentation
Dakotas Parent Meeting PresentationPaul OBriant
 
Drucker chapter 3
Drucker chapter 3Drucker chapter 3
Drucker chapter 3detjen
 
Fredrick Ishengoma - A Novel Design of IEEE 802.15.4 and Solar Based Autonomo...
Fredrick Ishengoma - A Novel Design of IEEE 802.15.4 and Solar Based Autonomo...Fredrick Ishengoma - A Novel Design of IEEE 802.15.4 and Solar Based Autonomo...
Fredrick Ishengoma - A Novel Design of IEEE 802.15.4 and Solar Based Autonomo...Fredrick Ishengoma
 
Staying safe online
Staying safe onlineStaying safe online
Staying safe onlinePaul OBriant
 
Fredrick Ishengoma - HDFS+- Erasure Coding Based Hadoop Distributed File System
Fredrick Ishengoma -  HDFS+- Erasure Coding Based Hadoop Distributed File SystemFredrick Ishengoma -  HDFS+- Erasure Coding Based Hadoop Distributed File System
Fredrick Ishengoma - HDFS+- Erasure Coding Based Hadoop Distributed File SystemFredrick Ishengoma
 

Destaque (19)

Chapter 13
Chapter 13Chapter 13
Chapter 13
 
Arte a medio dibujar
Arte a medio dibujarArte a medio dibujar
Arte a medio dibujar
 
Cyber safety, technology and the church
Cyber safety, technology and the churchCyber safety, technology and the church
Cyber safety, technology and the church
 
Adam Mtaho & Fredrick Ishengoma - Factors Affecting QoS in Tanzania Cellular ...
Adam Mtaho & Fredrick Ishengoma - Factors Affecting QoS in Tanzania Cellular ...Adam Mtaho & Fredrick Ishengoma - Factors Affecting QoS in Tanzania Cellular ...
Adam Mtaho & Fredrick Ishengoma - Factors Affecting QoS in Tanzania Cellular ...
 
Luxembourg Blockchain Meetup 13 July 2016 - Bertolo
Luxembourg Blockchain Meetup 13 July 2016 - BertoloLuxembourg Blockchain Meetup 13 July 2016 - Bertolo
Luxembourg Blockchain Meetup 13 July 2016 - Bertolo
 
Online safety
Online safetyOnline safety
Online safety
 
Chapter 6
Chapter 6Chapter 6
Chapter 6
 
Online landscape
Online landscapeOnline landscape
Online landscape
 
Collaborative archietyped for ipv4
Collaborative archietyped for ipv4Collaborative archietyped for ipv4
Collaborative archietyped for ipv4
 
Deploying the producer consumer problem using homogeneous modalities
Deploying the producer consumer problem using homogeneous modalitiesDeploying the producer consumer problem using homogeneous modalities
Deploying the producer consumer problem using homogeneous modalities
 
Chapter 4
Chapter 4Chapter 4
Chapter 4
 
Plenary Session - Technology and the Church
Plenary Session - Technology and the ChurchPlenary Session - Technology and the Church
Plenary Session - Technology and the Church
 
Dakotas Parent Meeting Presentation
Dakotas Parent Meeting PresentationDakotas Parent Meeting Presentation
Dakotas Parent Meeting Presentation
 
Online resources
Online resourcesOnline resources
Online resources
 
Drucker chapter 3
Drucker chapter 3Drucker chapter 3
Drucker chapter 3
 
Fredrick Ishengoma - A Novel Design of IEEE 802.15.4 and Solar Based Autonomo...
Fredrick Ishengoma - A Novel Design of IEEE 802.15.4 and Solar Based Autonomo...Fredrick Ishengoma - A Novel Design of IEEE 802.15.4 and Solar Based Autonomo...
Fredrick Ishengoma - A Novel Design of IEEE 802.15.4 and Solar Based Autonomo...
 
Using tech safely
Using tech safelyUsing tech safely
Using tech safely
 
Staying safe online
Staying safe onlineStaying safe online
Staying safe online
 
Fredrick Ishengoma - HDFS+- Erasure Coding Based Hadoop Distributed File System
Fredrick Ishengoma -  HDFS+- Erasure Coding Based Hadoop Distributed File SystemFredrick Ishengoma -  HDFS+- Erasure Coding Based Hadoop Distributed File System
Fredrick Ishengoma - HDFS+- Erasure Coding Based Hadoop Distributed File System
 

Semelhante a Fredrick Ishengoma - Online Social Networks and Terrorism 2.0 in Developing Countries

A Systematic Survey on Detection of Extremism in Social Media
A Systematic Survey on Detection of Extremism in Social MediaA Systematic Survey on Detection of Extremism in Social Media
A Systematic Survey on Detection of Extremism in Social MediaRSIS International
 
Brown and Beige Aesthetic Vintage Group Project Presentation.pdf
Brown and Beige Aesthetic Vintage Group Project Presentation.pdfBrown and Beige Aesthetic Vintage Group Project Presentation.pdf
Brown and Beige Aesthetic Vintage Group Project Presentation.pdfvenuspatatag4
 
64The Empire Strikes Back Social Media Uprisings and .docx
64The Empire Strikes Back Social Media Uprisings and .docx64The Empire Strikes Back Social Media Uprisings and .docx
64The Empire Strikes Back Social Media Uprisings and .docxevonnehoggarth79783
 
Twitter turns ten: its use to date in disaster management
Twitter turns ten: its use to date in disaster managementTwitter turns ten: its use to date in disaster management
Twitter turns ten: its use to date in disaster managementNeil Dufty
 
CS322 Network Analysis.docx
CS322 Network Analysis.docxCS322 Network Analysis.docx
CS322 Network Analysis.docxwrite31
 
The Reasons social media contributed to 2011 Egyptian Revolution
The Reasons social media contributed to 2011 Egyptian RevolutionThe Reasons social media contributed to 2011 Egyptian Revolution
The Reasons social media contributed to 2011 Egyptian RevolutionWaqas Tariq
 
Twitter And Social Justice
Twitter And Social JusticeTwitter And Social Justice
Twitter And Social JusticeJodi Sperber
 
A review for the online social networks literature
A review for the online social networks literatureA review for the online social networks literature
A review for the online social networks literatureAlexander Decker
 
A review for the online social networks literature
A review for the online social networks literatureA review for the online social networks literature
A review for the online social networks literatureAlexander Decker
 
The Influcence of Twitter on Academic Environment
The Influcence of Twitter on Academic EnvironmentThe Influcence of Twitter on Academic Environment
The Influcence of Twitter on Academic EnvironmentMartin Ebner
 
social networking NMT
social networking NMTsocial networking NMT
social networking NMTNalini Prasad
 
Fake news detection for Arabic headlines-articles news data using deep learning
Fake news detection for Arabic headlines-articles news data  using deep learningFake news detection for Arabic headlines-articles news data  using deep learning
Fake news detection for Arabic headlines-articles news data using deep learningIJECEIAES
 
Social Media in light of Sociology
Social Media in light of SociologySocial Media in light of Sociology
Social Media in light of SociologyIsmakhalid1
 
POLITICAL OPINION ANALYSIS IN SOCIAL NETWORKS: CASE OF TWITTER AND FACEBOOK
POLITICAL OPINION ANALYSIS IN SOCIAL  NETWORKS: CASE OF TWITTER AND FACEBOOK POLITICAL OPINION ANALYSIS IN SOCIAL  NETWORKS: CASE OF TWITTER AND FACEBOOK
POLITICAL OPINION ANALYSIS IN SOCIAL NETWORKS: CASE OF TWITTER AND FACEBOOK dannyijwest
 
POLITICAL OPINION ANALYSIS IN SOCIAL NETWORKS: CASE OF TWITTER AND FACEBOOK
POLITICAL OPINION ANALYSIS IN SOCIAL NETWORKS: CASE OF TWITTER AND FACEBOOKPOLITICAL OPINION ANALYSIS IN SOCIAL NETWORKS: CASE OF TWITTER AND FACEBOOK
POLITICAL OPINION ANALYSIS IN SOCIAL NETWORKS: CASE OF TWITTER AND FACEBOOKIJwest
 
mmmmmmmmmmmmmmmm
mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm
mmmmmmmmmmmmmmmmRohit440277
 

Semelhante a Fredrick Ishengoma - Online Social Networks and Terrorism 2.0 in Developing Countries (20)

A Systematic Survey on Detection of Extremism in Social Media
A Systematic Survey on Detection of Extremism in Social MediaA Systematic Survey on Detection of Extremism in Social Media
A Systematic Survey on Detection of Extremism in Social Media
 
Brown and Beige Aesthetic Vintage Group Project Presentation.pdf
Brown and Beige Aesthetic Vintage Group Project Presentation.pdfBrown and Beige Aesthetic Vintage Group Project Presentation.pdf
Brown and Beige Aesthetic Vintage Group Project Presentation.pdf
 
64The Empire Strikes Back Social Media Uprisings and .docx
64The Empire Strikes Back Social Media Uprisings and .docx64The Empire Strikes Back Social Media Uprisings and .docx
64The Empire Strikes Back Social Media Uprisings and .docx
 
Twitter turns ten: its use to date in disaster management
Twitter turns ten: its use to date in disaster managementTwitter turns ten: its use to date in disaster management
Twitter turns ten: its use to date in disaster management
 
CS322 Network Analysis.docx
CS322 Network Analysis.docxCS322 Network Analysis.docx
CS322 Network Analysis.docx
 
H018144450
H018144450H018144450
H018144450
 
Edrd 3160 chowdhury
Edrd 3160 chowdhuryEdrd 3160 chowdhury
Edrd 3160 chowdhury
 
The Reasons social media contributed to 2011 Egyptian Revolution
The Reasons social media contributed to 2011 Egyptian RevolutionThe Reasons social media contributed to 2011 Egyptian Revolution
The Reasons social media contributed to 2011 Egyptian Revolution
 
Twitter And Social Justice
Twitter And Social JusticeTwitter And Social Justice
Twitter And Social Justice
 
B4111219.pdf
B4111219.pdfB4111219.pdf
B4111219.pdf
 
A review for the online social networks literature
A review for the online social networks literatureA review for the online social networks literature
A review for the online social networks literature
 
A review for the online social networks literature
A review for the online social networks literatureA review for the online social networks literature
A review for the online social networks literature
 
The Influcence of Twitter on Academic Environment
The Influcence of Twitter on Academic EnvironmentThe Influcence of Twitter on Academic Environment
The Influcence of Twitter on Academic Environment
 
social networking NMT
social networking NMTsocial networking NMT
social networking NMT
 
Fake news detection for Arabic headlines-articles news data using deep learning
Fake news detection for Arabic headlines-articles news data  using deep learningFake news detection for Arabic headlines-articles news data  using deep learning
Fake news detection for Arabic headlines-articles news data using deep learning
 
Social Media in light of Sociology
Social Media in light of SociologySocial Media in light of Sociology
Social Media in light of Sociology
 
Kottler Thesis 2011
Kottler Thesis 2011Kottler Thesis 2011
Kottler Thesis 2011
 
POLITICAL OPINION ANALYSIS IN SOCIAL NETWORKS: CASE OF TWITTER AND FACEBOOK
POLITICAL OPINION ANALYSIS IN SOCIAL  NETWORKS: CASE OF TWITTER AND FACEBOOK POLITICAL OPINION ANALYSIS IN SOCIAL  NETWORKS: CASE OF TWITTER AND FACEBOOK
POLITICAL OPINION ANALYSIS IN SOCIAL NETWORKS: CASE OF TWITTER AND FACEBOOK
 
POLITICAL OPINION ANALYSIS IN SOCIAL NETWORKS: CASE OF TWITTER AND FACEBOOK
POLITICAL OPINION ANALYSIS IN SOCIAL NETWORKS: CASE OF TWITTER AND FACEBOOKPOLITICAL OPINION ANALYSIS IN SOCIAL NETWORKS: CASE OF TWITTER AND FACEBOOK
POLITICAL OPINION ANALYSIS IN SOCIAL NETWORKS: CASE OF TWITTER AND FACEBOOK
 
mmmmmmmmmmmmmmmm
mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm
mmmmmmmmmmmmmmmm
 

Último

Developer Data Modeling Mistakes: From Postgres to NoSQL
Developer Data Modeling Mistakes: From Postgres to NoSQLDeveloper Data Modeling Mistakes: From Postgres to NoSQL
Developer Data Modeling Mistakes: From Postgres to NoSQLScyllaDB
 
Artificial intelligence in cctv survelliance.pptx
Artificial intelligence in cctv survelliance.pptxArtificial intelligence in cctv survelliance.pptx
Artificial intelligence in cctv survelliance.pptxhariprasad279825
 
Take control of your SAP testing with UiPath Test Suite
Take control of your SAP testing with UiPath Test SuiteTake control of your SAP testing with UiPath Test Suite
Take control of your SAP testing with UiPath Test SuiteDianaGray10
 
How AI, OpenAI, and ChatGPT impact business and software.
How AI, OpenAI, and ChatGPT impact business and software.How AI, OpenAI, and ChatGPT impact business and software.
How AI, OpenAI, and ChatGPT impact business and software.Curtis Poe
 
TrustArc Webinar - How to Build Consumer Trust Through Data Privacy
TrustArc Webinar - How to Build Consumer Trust Through Data PrivacyTrustArc Webinar - How to Build Consumer Trust Through Data Privacy
TrustArc Webinar - How to Build Consumer Trust Through Data PrivacyTrustArc
 
Nell’iperspazio con Rocket: il Framework Web di Rust!
Nell’iperspazio con Rocket: il Framework Web di Rust!Nell’iperspazio con Rocket: il Framework Web di Rust!
Nell’iperspazio con Rocket: il Framework Web di Rust!Commit University
 
Connect Wave/ connectwave Pitch Deck Presentation
Connect Wave/ connectwave Pitch Deck PresentationConnect Wave/ connectwave Pitch Deck Presentation
Connect Wave/ connectwave Pitch Deck PresentationSlibray Presentation
 
Anypoint Exchange: It’s Not Just a Repo!
Anypoint Exchange: It’s Not Just a Repo!Anypoint Exchange: It’s Not Just a Repo!
Anypoint Exchange: It’s Not Just a Repo!Manik S Magar
 
Scanning the Internet for External Cloud Exposures via SSL Certs
Scanning the Internet for External Cloud Exposures via SSL CertsScanning the Internet for External Cloud Exposures via SSL Certs
Scanning the Internet for External Cloud Exposures via SSL CertsRizwan Syed
 
Merck Moving Beyond Passwords: FIDO Paris Seminar.pptx
Merck Moving Beyond Passwords: FIDO Paris Seminar.pptxMerck Moving Beyond Passwords: FIDO Paris Seminar.pptx
Merck Moving Beyond Passwords: FIDO Paris Seminar.pptxLoriGlavin3
 
Gen AI in Business - Global Trends Report 2024.pdf
Gen AI in Business - Global Trends Report 2024.pdfGen AI in Business - Global Trends Report 2024.pdf
Gen AI in Business - Global Trends Report 2024.pdfAddepto
 
Designing IA for AI - Information Architecture Conference 2024
Designing IA for AI - Information Architecture Conference 2024Designing IA for AI - Information Architecture Conference 2024
Designing IA for AI - Information Architecture Conference 2024Enterprise Knowledge
 
TeamStation AI System Report LATAM IT Salaries 2024
TeamStation AI System Report LATAM IT Salaries 2024TeamStation AI System Report LATAM IT Salaries 2024
TeamStation AI System Report LATAM IT Salaries 2024Lonnie McRorey
 
"LLMs for Python Engineers: Advanced Data Analysis and Semantic Kernel",Oleks...
"LLMs for Python Engineers: Advanced Data Analysis and Semantic Kernel",Oleks..."LLMs for Python Engineers: Advanced Data Analysis and Semantic Kernel",Oleks...
"LLMs for Python Engineers: Advanced Data Analysis and Semantic Kernel",Oleks...Fwdays
 
SAP Build Work Zone - Overview L2-L3.pptx
SAP Build Work Zone - Overview L2-L3.pptxSAP Build Work Zone - Overview L2-L3.pptx
SAP Build Work Zone - Overview L2-L3.pptxNavinnSomaal
 
SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024Lorenzo Miniero
 
The Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and ConsThe Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and ConsPixlogix Infotech
 
"Debugging python applications inside k8s environment", Andrii Soldatenko
"Debugging python applications inside k8s environment", Andrii Soldatenko"Debugging python applications inside k8s environment", Andrii Soldatenko
"Debugging python applications inside k8s environment", Andrii SoldatenkoFwdays
 

Último (20)

Developer Data Modeling Mistakes: From Postgres to NoSQL
Developer Data Modeling Mistakes: From Postgres to NoSQLDeveloper Data Modeling Mistakes: From Postgres to NoSQL
Developer Data Modeling Mistakes: From Postgres to NoSQL
 
Artificial intelligence in cctv survelliance.pptx
Artificial intelligence in cctv survelliance.pptxArtificial intelligence in cctv survelliance.pptx
Artificial intelligence in cctv survelliance.pptx
 
E-Vehicle_Hacking_by_Parul Sharma_null_owasp.pptx
E-Vehicle_Hacking_by_Parul Sharma_null_owasp.pptxE-Vehicle_Hacking_by_Parul Sharma_null_owasp.pptx
E-Vehicle_Hacking_by_Parul Sharma_null_owasp.pptx
 
Take control of your SAP testing with UiPath Test Suite
Take control of your SAP testing with UiPath Test SuiteTake control of your SAP testing with UiPath Test Suite
Take control of your SAP testing with UiPath Test Suite
 
How AI, OpenAI, and ChatGPT impact business and software.
How AI, OpenAI, and ChatGPT impact business and software.How AI, OpenAI, and ChatGPT impact business and software.
How AI, OpenAI, and ChatGPT impact business and software.
 
TrustArc Webinar - How to Build Consumer Trust Through Data Privacy
TrustArc Webinar - How to Build Consumer Trust Through Data PrivacyTrustArc Webinar - How to Build Consumer Trust Through Data Privacy
TrustArc Webinar - How to Build Consumer Trust Through Data Privacy
 
Nell’iperspazio con Rocket: il Framework Web di Rust!
Nell’iperspazio con Rocket: il Framework Web di Rust!Nell’iperspazio con Rocket: il Framework Web di Rust!
Nell’iperspazio con Rocket: il Framework Web di Rust!
 
Connect Wave/ connectwave Pitch Deck Presentation
Connect Wave/ connectwave Pitch Deck PresentationConnect Wave/ connectwave Pitch Deck Presentation
Connect Wave/ connectwave Pitch Deck Presentation
 
Anypoint Exchange: It’s Not Just a Repo!
Anypoint Exchange: It’s Not Just a Repo!Anypoint Exchange: It’s Not Just a Repo!
Anypoint Exchange: It’s Not Just a Repo!
 
Scanning the Internet for External Cloud Exposures via SSL Certs
Scanning the Internet for External Cloud Exposures via SSL CertsScanning the Internet for External Cloud Exposures via SSL Certs
Scanning the Internet for External Cloud Exposures via SSL Certs
 
Merck Moving Beyond Passwords: FIDO Paris Seminar.pptx
Merck Moving Beyond Passwords: FIDO Paris Seminar.pptxMerck Moving Beyond Passwords: FIDO Paris Seminar.pptx
Merck Moving Beyond Passwords: FIDO Paris Seminar.pptx
 
Gen AI in Business - Global Trends Report 2024.pdf
Gen AI in Business - Global Trends Report 2024.pdfGen AI in Business - Global Trends Report 2024.pdf
Gen AI in Business - Global Trends Report 2024.pdf
 
Designing IA for AI - Information Architecture Conference 2024
Designing IA for AI - Information Architecture Conference 2024Designing IA for AI - Information Architecture Conference 2024
Designing IA for AI - Information Architecture Conference 2024
 
TeamStation AI System Report LATAM IT Salaries 2024
TeamStation AI System Report LATAM IT Salaries 2024TeamStation AI System Report LATAM IT Salaries 2024
TeamStation AI System Report LATAM IT Salaries 2024
 
DMCC Future of Trade Web3 - Special Edition
DMCC Future of Trade Web3 - Special EditionDMCC Future of Trade Web3 - Special Edition
DMCC Future of Trade Web3 - Special Edition
 
"LLMs for Python Engineers: Advanced Data Analysis and Semantic Kernel",Oleks...
"LLMs for Python Engineers: Advanced Data Analysis and Semantic Kernel",Oleks..."LLMs for Python Engineers: Advanced Data Analysis and Semantic Kernel",Oleks...
"LLMs for Python Engineers: Advanced Data Analysis and Semantic Kernel",Oleks...
 
SAP Build Work Zone - Overview L2-L3.pptx
SAP Build Work Zone - Overview L2-L3.pptxSAP Build Work Zone - Overview L2-L3.pptx
SAP Build Work Zone - Overview L2-L3.pptx
 
SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024
 
The Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and ConsThe Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and Cons
 
"Debugging python applications inside k8s environment", Andrii Soldatenko
"Debugging python applications inside k8s environment", Andrii Soldatenko"Debugging python applications inside k8s environment", Andrii Soldatenko
"Debugging python applications inside k8s environment", Andrii Soldatenko
 

Fredrick Ishengoma - Online Social Networks and Terrorism 2.0 in Developing Countries

  • 1. Online Social Networks and Terrorism 2.0 in Developing Countries Fredrick Romanus Ishengoma College of Informatics and Virtual Education, The University of Dodoma, Dodoma, Tanzania. ishengomaf@gmail.com Abstract The advancement in technology has brought a new era in terrorism where Online Social Networks (OSNs) have become a major platform of communication with wide range of usage from message channeling to propaganda and recruitment of new followers in terrorist groups. Meanwhile, during the terrorist attacks people use OSNs for information exchange, mobilizing and uniting and raising money for the victims. This paper critically analyses the specific usage of OSNs in the times of terrorisms attacks in developing countries. We crawled and used Twitter’s data during Westgate shopping mall terrorist attack in Nairobi, Kenya. We then analyzed the number of tweets, geo-location of tweets, demographics of the users and whether users in developing countries tend to tweet, retweet or reply during the event of a terrorist attack. We define new metrics (reach and impression of the tweet) and present the models for calculating them. The study findings show that, users from developing countries tend to tweet more at the first and critical times of the terrorist occurrence. Moreover, large number of tweets originated from the attacked country (Kenya) with 73% from men and 23% from women where original posts had a most number of tweets followed by replies and retweets. Keywords: Developing Countries, Online Social Networks, Terrorism 2.0, Twitter and Westgate. I. Introduction Online Social Networks (OSNs) example Twitter, Facebook, and YouTube have emerged as major means of communication for people in sharing and exchanging information on a wide variety of real-world events. As technology and Internet advances in developing countries, users from developing regions are also increasing in using OSNs (Reda, 2012). Numerous studies have shown that users from developing countries are spending a significant amount of time in OSNs (Karel 2007; Reda 2011). Another OSNs study (Pew Research Center, 2010) showed many people in developing countries do not go online, however when they have the opportunity to go online, they tend to use online social networking sites. For example, one-in-five Kenyans (19%) participate in online social networking, while just 5% use the Internet but do not participate. Of the users that go online in developing countries, the demographics have shown a double-digit difference in gender gap where more men tend to go online compared to women (Pew Research Center, 2010; Intel, 2013). A recently study by Intel showed that on average, 23% fewer women than men are online in developing countries (Intel, 2013). While the OSNs users can use the technology positively for communication and information exchange, yet the same technology can also be used negatively as a tool for terrorism 2.0. Terrorism 2.0 is the use of web 2.0 applications and semantic technologies in assisting or
  • 2. performing terrorist acts. With web 2.0, terrorist are able to connect them using social networks for sharing information, disseminate propaganda, recruiting new members and even planning an attack. For example, Al-Shabaab, a terrorist group based in Somalia, used Twitter during a Westgate terrorist attack in Nairobi to disseminate information and claiming responsibility of the attack. Meanwhile, during terrorist attacks people have been using these OSNs to break the news, provide information with rich media content and uniting people for providing help and fundraising for the victims. For example, during the Westgate attack Twitter was used to mobilize the country for blood donation, money donation as well as keeping the peace. People used the hashtag #WeAreOne for uniting the country through updates and insights and raising money for the victims. The aim of this paper is to analyze how OSNs is being used during the event of a terrorist attacks in developing countries along. We perform activity analysis of Twitter after the Westgate attack in Nairobi. Moreover, we present the OSNs challenges and opportunities in relation to terrorism 2.0. The rest of the paper is organized as follows: We start by providing related work in section 2. Section 3 is dedicated to the background of terrorism 2.0 and OSNs. Section 4 discuses Twitter in the era of Terrorism 2.0 with subsections on how people use Twitter and Twitter as a terrorist assistance tool. Data collection is discussed in Section 5. Section 6 discuses and analyses the findings of the study. We conclude in Section 7. II. Related Work In this section, we provide an overview of various studies that are related to our research work. A number of studies (Murthy, 2010; Mendoza, 2010, Stollberg, 2012; Nagar, 2012; Hossmann, 2012) have focused their work on the usage of OSNs during disasters like floods and earthquakes and in facilitating event detection and responses to emergency situations (Becker, Naaman, and Gravano 2011; Li, Sun, and Datta 2012; Li et al. 2012; Weng et al. 2011). Weimann (Weimann, 2011) describes how the advances of technology has changed terrorist online communication from one-directional to bi-directional with interactive capabilities like chat-rooms, online social networking sites, video-sharing sites. (Veerasamy, 2012) represented the functions and methods that terrorists have come to rely on through the Information and Communication Technology (ICT) infrastructure. The discussion sheds light on the technical and practical role that ICT infrastructure plays in the assistance of terrorism. (Gupta, 2011) attempt to characterize and extract patterns of activity of users on Twitter during a crisis based on the Mumbai terrorist attack. The study attempted to characterize and extract patterns of activity of users on Twitter during a terrorist situation. Another close related work is by Oh and Agrawal, (Oh, 2011). They analyzed the Twitter stream during the 2008 Mumbai terrorist attacks. The study applied social awareness theory to show how information available on OSNs during the attacks aided the terrorists’ decision making.
  • 3. While some of the studies have the similar objectives with our study, our study remains unique as it focuses on a OSNs usage during terrorists attack in a developing country context. III. Terrorism 2.0 and Online Social Networks In this section we will provide an introductory overview of Terrorism 2.0 and Online Social Networks (OSNs) and how they are related. A. Terrorism 2.0 As Information and Communication Technologies (ICTs) advances and transform how we live, it also changes the terrorism era. Advances in IT has brought a new era of Terrorism 2.0 where terrorist now make use of high advancement of IT to accomplish their goals. OSNs have now been used by terrorists for communication, recruiting new members, transmitting training videos and materials and propaganda. For example, one terrorist website provide details on how to make Improvised Explosive Devices (IEDs), a bomb that can be made from locally available materials. Other terrorist websites have been distributing materials (tutorials and books) online on how to make poisons, bombs and conduct a terrorist attack. Some of the popular terrorist books that circulate online are The Mujahideen Poisons Handbook and The Anarchist’s Cookbook. B. Online Social Networks Online Social Networking Sites (OSNs) are kind of social media that gives ability online user to make a profile with his information and enable users to share and exchange messages and multimedia content (Boyd & Ellison, 2008). Some examples of popular social networks include Facebook, Twitter, YouTube and Flickr. They depend on peer-to-peer (P2P) networks that are cooperative, distributed, and community driven. Within the OSNs users can create groups for people with common interest to share information and communicate privately. Recently, terrorists have changed from its traditional ways of communicating to adapt the use of OSNs as their platform of communication. OSNs has opened a new way to terrorists enabling them to communicate easily and more secure, disseminate information, propaganda and training materials, organize attacks, recruiting new members and to seek sympathy to the public for their actions worldwide. IV. Twitter in the Era of Terrorism 2.0 With registered users more than 500 million worldwide as of October 2013, Twitter is one of the most popular online social networks available. Twitter offers exchange of short messages called Tweets of up to 140 characters long between its users. Hashtags are words prefixed with ‘#’ used by Twitter users to describe a subject (e.g. #BreakingNews). Common practice of responding to a tweet has evolved into well-defined mark-up culture: RT stands for Retweet. A retweet is a message from one user that is forwarded by a second user. The retweet mechanism
  • 4. empowers users to spread information of their choice beyond the reach of the original tweet’s followers. A message from one Twitter user that is a response to Twitter user’s message is called a Reply. Being a follower on Twitter means that the user receives all the tweets from those the user follows. We opted to use Twitter as our choice of OSN for this study due to its availability of data. A. How people use Twitter? Studies have shown that people use Twitter for different purposes (Java, 2007; Ramage, 2010; Naaman, 2010) studied the aims of 94,000 Twitter users with more than 1.3 million tweets and concluded that users make use of Twitter in the following major areas: (i) Chatting. Most Twitter users are for discussion of day-to-day activities. (ii) Conversations. Some of the Twitter users engage in the conversation using replies mechanism. (iii) Information exchange/Sharing. Twitter users share and exchange information through Twitter posts contains URLs. (iv) News. Reporting and commenting on breaking news and latest news is another type of people’s usage in Twitter. B. Twitter as a Terrorist Assistance Tool OSN is a suitable platform for terrorists because of its easy access, little control from the governments, worldwide audience, anonymity (via fake profiles), fast flow of information, cheap development of OSN websites and multimedia platform (the capability to combine text, graphics, audio, video and downloading). With the current highly development of Information and Communication Technologies (ICTs) terrorist uses OSN for the following purposes: (i) Information exchange. Terrorist use OSN to communicate with worldwide audience than it was a decade before. Terrorists have become sophisticated in using anonymous/secret communications using encryption, steganography and anonymity softwares. Example, Al-Qaeda members have been using encryption softwares “Mujahedeen Secrets 1” and “Mujahedeen Secrets 2” to encrypt and secure their email communications. (ii) Recruiting and Training. A report by the institute of homeland security of the George Washington University (Homeland Security Institute, 2009) relays that the Internet has become crucial instrument in the hands of terrorists to spread their messages and recruit new supporters. Nowadays terrorists’ recruitment and training can be successfully offered via OSNs easily and anonymously unlike before, which required the physical meetings of trainees and trainers. Recruits are passing through a series of tests in password protected websites and restricted chat rooms before accepted and joining the terrorist group (Gerwehr, 2006). Tactics used includes the integration of terrorist acts in cartoons and music videos to attract the minors into terrorism. Also, video games that involve the acts of terrorism like mass suicide attack. (iii) Planning attacks. OSNs are used by terrorists to plan an attack due to its secure communication and fast message channeling.
  • 5. (iv) Fundraising. Through wire transfer and email address the groups are able to conduct a fundraising in OSNs. (v) Cyber-attack. Cyber-attack refers to the use of computer networking tools to attack other computer networks or national communications systems like government operations, transportation, and energy. (vi) Propaganda. Though these OSN have played a great role in the society, at the same time the terrorists is using them for their propaganda dissemination. These propaganda deals with delivering ideological, clarifications, explanations or campaign of terrorist actions. These can involve messages, demonstrations, magazines, audio and video footage of violent acts. On 16 March 2013, the propaganda arm of al-Qaeda, the Andalus Foundation, created a twitter account (@Andalus_Media). The account has gained more than 14,500 followers while following 7 people inclusing the Somali terrorist group Al Shaabab. Al-Shabaab (Kimunguyi (2010), Ibrahim (2010)) also known as Harakat al-Shabaab al-Mujahideen (HSM) started their Twitter account in English as HSM Office on December 2011 using the Twitter handle ‘@HSMPress’ (https://twitter.com/#!/HSMPress). HSMPress is the press branch of Al-Shabaab (HSM). Since then they have been using Twitter to exaggerate their military accomplishments. Al-Shabaab has been in battle with Kenya (due to presence of Kenyan Army in Somalia) that has led to Westgate attack in September 2013 Nairobi. The terrorist group’s Twitter account has been repetitive suspended by Twitter due to violation of terms of service. Twitter’s terms of service state that users “may not publish or post direct, specific threats of violence against others.” However each time their account is suspended, they create new accounts with some slight variations on the same name such as @HSMPRESS1, @HSM_PressOffice, @HSM_PROffice and @HSM_PR. Figure. 1. Cover of Al-Shabaab’s English Twitter page as of 13 August 2013.
  • 6. Figure. 2. Example of Al-Shabaab’s Tweet during the Westgate attack. V. Data Our case study is the terrorist attack of Westgate shopping mall in Nairobi, Kenya on 21st September 2013. The attack lasted until 24th September resulting in at least 72 deaths and over 200 wounded people (Raidió Teilifís Éireann, 2013). The Islamist group Al-Shabaab claimed accountability for the terrorist attack. We used Twitter search API during the Westgate attack period when the text string ‘#Westgate’ was most active and Topsy (Topys, 2013), a certified Twitter partner that maintains the world’s largest index of tweets, numbering in hundreds of billions, dating back to May 2008. We crawled the data of the popular Twiter #hashtags that was used during the Westgate attack namely; #Westgate. The #Westgate hashtag was used in tweeting by both the terrorists and the civilians. We analyzed data between 21st and 27th to obtain the clear picture of the patterns. These data are analyzed to explore the following metrics: (i) Number of tweets during the terrorist attack. (ii) Whether users tend to tweet, retweet or reply in Twitter during the event of Westgate terrorist attack. (iii) What countries had the highest frequency of tweets during the Westgate terrorist attack. (iv) What are the demographics of the Twitter users during the Westgate terrorist attack and (v) What were the reachness and impressions of the tweets during the Westgate terrorist attack? VI. Findings and Discussion In this section we present our findings of the study and discussion. We begin by examining the number of tweets that were sent during the #Westgate attack. While there were many other hashtags used to discuss the terrorist attack in Twitter posts (like #Nairobi, #Kenya, #Terrorist), we chose the #Westgate hashtag since it was the most relevant one and standard one. We considered the number of tweets that uses only the hashtag ‘Westgate’.
  • 7. Figure. 3. Number of tweets during the #Westgate attack. Figure 3 shows the number of tweets tweeted using #Westgate hashtag during the Westgate attack period between 21st September. The number of tweets is observed to be high during the first hours of the terrorist attack and when the terrorist attack is in its peak. This is due to the Twitter’s real time nature i.e. the behaviour of Twitter users to post about events as they are happening. The tweets are observed to decrease as the terrorist attack ends. Figure 4. Geographical distribution of tweets during the #Westgate attack. Figure 4 shows the geographical distribution of tweets during the Westgate attack. From the figure it is observed that most of the tweets came from the developing countries. Kenya being the countries tweeted mostly about the attack, this could be because it is the attacked country. Also, a significant number of tweets is shown to have originated from US and UK. We then analyzed the Twitter data to find out, how many tweets were original posts, retweets or replies using the keyword #Westgate.
  • 8. Figure 5. Sharing of tweets (original, retweets and replies) during the #Westgate attack. Figure 5 shows the sharing of Twitter posts during the Westgate attack. From the figure it is observed that most of the tweets during the attack were original posts (65%), followed by retweets (27%) and replies (8%). In figure 6 we analyzed the reach and impression of #Westgate tweets during the terrorist attack. We define reach, as the number of unique followers that a user has that is, the unique people who a tweet could potentially get to. We define impression as the number of times a user posts that is, how many times followers would see these posts. Let N be the number of followers a Twitter user has and t the number of times a tweet is tweeted. Reach is given by N whereby Nt gives impression. For example, if a Twitter user has 300 followers In figure 6 we analysed the reach and impression of #Westgate tweets during the terrorist attack. We define reach, as the number of unique followers that a user has that is, the unique people who a tweet could potentially get to. We define impression as the number of times a user posts that is, how many times followers would see these posts. Let N be the number of followers a Twitter user has and t the number of times a tweet is tweeted. Reach is given by N whereby Nt gives impression. For example, if a Twitter user has 300 followers and tweet 3 times then tweet’s reach is 300 and tweet’s impression is 900 (since 300 followers saw the tweet thrice).
  • 9. Figure 6. Reach and Impression of tweets during the #Westgate attack. We then analyzed the demography of the Twitter posts during the #Westgate attack. In Figure 7 we could see the percentage of male and female who tweeted about the terrorist attack using #Westgate hashtag. Males are observed to tweet more than females. 73% of the #Westgate tweets are observed to be from males while 27% of the #Westgate tweets are from females. This could be due to the gender gap in developing countries where according to International Telecommunication Union (ITU, 2013), 16% fewer women than men use the Internet in developing countries. Figure 7. Demography of Twitter posts during the #Westgate attack. VII. Conclusion
  • 10. In this paper, we analyzed the usage of Online Social Networks (OSNs) in the event of a terrorist attack with a case study of a Westgate shopping mall attack in Nairobi, Kenya. We used different metrics like number of tweets, whether users in developing countries tended to tweet, retweet or reply, demographics, geo-location and we defined new metrics (reach and impression of the tweet) and presented their models. While the developing countries are faced by many limitations in using OSNs such as unreliable power and poor Internet connection, still the study finding challenges the traditional media of reporting during disasters like terrorists attacks. We recommend centers globally to make full use of the OSNs for crisis communication in order to save more lives during such. References i. Aditi Gupta, Ponnurangam Kumaraguru, Twitter Explodes with Activity in Mumbai Blasts! A Lifeline or an Unmonitored Daemon in the Lurking? PSOSM '12 Proceedings of the 1st Workshop on Privacy and Security in Online Social Media, 2012. ii. Azarias Reda, Sam Shah, Mitur Tiwali, Anita Lillie, Brian Noble, Social Networking in Developing Regions, Fifth International Conference on Information and Communication Technologies and Development (ICTD 2012), 2012. iii. Azarias Reda, Edward Cutrell, and Brian Noble, Towards Improved Web Acceleration: Leveraging the Personal Web. In Pro- ceedings of the 5th ACM Workshop on Networked Systems for Developing Regions (NSDR), pages 57 - 62, Bethesda, Maryland, USA, June 2011. iv. Beate Stollberg, Tom de Groeve, The Use of Social Media within the Global Disaster Alert and Coordination System (GDACS), WWW– SWDM'12 Workshop April 16–20, 2012, Lyon, France, 2012. v. Becker, H.; Naaman, M.; and Gravano, L, Beyond Trending Topics: Real-world Event Identification on Twitter. In Proc. of WSM, 2011. vi. Dhiraj Murthy & Scott A. Longwell, Twitter and Disasters: The uses of Twitter during the 2010 Pakistan floods, May 2012. vii. Gabriel Weimann, Lone Wolves in Cyberspace, Journal of Terrorism Research, Volume 3, Issue 2, 2012. viii. Gabriel Wimann, Al Qaeda Has Sent You A Friend Request: Terrorists Using Online Social Networking, Israeli Communication Association, 2011. ix. Homeland Security Institute (2009), The Internet as a Terrorist Tool for Recruitment and Radicalization of Youth, US Department of Homeland Security, Science and Technology Directorate.
  • 11. x. Ibrahim, M. (2010), Somalia and Global Terrorism: A Growing Connection? Journal of Contemporary African studies, Volume 28:3, pp.283-295. xi. Java, A., X. Song, T. Finin, and B. Tseng, Why We Twitter: Understanding Microblogging Usage and Communities, In WebKDD/SNA-KDD ’07: Proceedings of the 9th WebKDD and 1st SNA-KDD 2007 Workshop on Web Mining and Social Network Analysis, New York, NY, USA, pp. 56–65. ACM, 2007. xii. Karel Matthee, Gregory Mweemba, Adrian Pais, Gertjan van Stam, and Marijn Rijken, Bringing Internet Connectivity to Rural Zambia Using a Collaborative Approach, In Proceedings of the 2nd ACM International Conference on Information and Communication Technologies and Development (ICTD), pages 47–58, Bangalore, India, December 2007. xiii. Li, C.; Sun, A.; and Datta, A. Twevent, Segment-based Event De tection from Tweets. In Proc. of CIKM, 2012. xiv. Li, R.; Lei, K. H.; Khadiwala, R.; and Chang, K. C.-C. TEDAS: A Twitter-based Event Detection and Analysis System. In Proc. of ICDE, 2012. xv. Naaman, M., J. Boase, and C.-H. Lai, Is it Really about Me?: Message Content in Social Awareness Streams, In Proceedings of the 2010 ACM Conference on Computer Supported Cooperative Work, CSCW ’10, New York, NY, USA, pp. 189–192. ACM, 2010. xvi. Marcelo Mendoza, Barbara Poblete, and Carlos Castillo. Twitter Under Crisis: Can We Trust What We RT? In 1st Workshop on Social Media Analytics (SOMA ’10). ACM Press, July 2010. xvii. Onook Oh, Manish Agrawal, and H. Raghav Rao. Information Control and Terrorism: Tracking the Mumbai Terrorist Attack through Twitter. Information Systems Frontiers, 13(1):33–43, 2011. xviii. Patrick Kimunguyi (2010), Terrorism and Counter Terrorism in East Africa, Global Terrorism Centre, 2010. xix. Pew Research Center. Global Publics Embrace Social Networking. Pew Global Attitudes Project, 2010. xx. Raidió Teilifís Éireann, Kenyan Military Frees Most Hostages at Mall, 23 September 2013. Retrieved 24 September 2013. xxi. Ramage, D., S. Dumais, and D. Liebling, Characterizing Microblogs with Topic Models. In ICWSM, 2010.
  • 12. xxii. Seema Nagar, Aaditeshwar Seth, Anupam Joshi, Characterization of Social Media Response to Natural Disasters), WWW– SWDM'12 Workshop April 16–20, 2012, Lyon, France, 2012. xxiii. Scott Gerwehr and Sarah Daly (2006), Al-Qaida: Terrorist Selection and Recruitment, in The McGraw-Hill Homeland Security Handbook, David Kamien, ed. (New York, McGraw-Hill), pp. 83. xxiv. Theus Hossmann, Paolo Carta, Dominik Schatzmann, and Franck Legendre, Per Gunningberg, Christian Rohner, Twitter in Disaster Mode: Security Architecture, Proceedings of the Special Workshop on Internet and Disasters. Tokyo, Japan: ACM, 2011. xxv. Weng, J.; Yao, Y.; Leonardi, E.; and Lee, F. Event Detection in Twitter. In Proc. of WSM, 2011