Online Library

Online platforms are used extensively as a propaganda
tool to convince young people to support the
various groups fighting in Iraq and Syria. Many individuals
outside of the conflict partake in propaganda
efforts on social media, using their profiles to provide
electronic support to ISIS and other extremist
groups. An analysis of various profiles indicates that
those engaged in the Syria conflict use their profile
to disseminate information about the conflict, which
can be used for propaganda. The typical feature observed
across these profiles is the virtual association
between them.

The 8th Euromed Survey conducted by the European Institute of the Mediterranean touches
upon a number of important and complex issues related to violent extremism in the EuroMediterranean
region, including the question of the context and drivers through which violent
extremism can prosper. Echoing some of the results, this article looks into propaganda as a
tool of extremist ideologies and how to counter it.

This article’s objective is to categorize potential jihadists in Europe and provide an overview of contemporary methods for their recruitment. Taking into account the ubiquity of the Internet and social networking platforms, and the fact that younger generations are spending an ever increasing amount of time using contemporary communication technology, this article focuses on those recruitment methods that make use of social networking platforms and mobile applications for the spread of extremist propaganda, as well as for communication with potential adherents. An analysis of the age structure of individuals involved in the planning and carrying out of terrorist acts in Europe from November of 2015 to September of 2017 supports a hypothesis that contemporary recruitment methods are especially effective in targeting a younger demographic. In addition, this article negates the importance of traditional physical exposure to radical behavior, which serves to explain the increasing number of terrorist attacks in Europe conducted by radicalized citizens of European countries.

Steganography is the art and science of
hiding the fact that communication is taking place by
hiding information in other information’ (Johnson).
According to nameless “U.S. officials and experts”
and “U.S. and foreign officials,” terrorist groups
are “hiding maps and photographs of terrorist
targets and posting instructions for terrorist
activities on sports chat rooms, pornographic
bulletin boards and other Web sites”. This paper
informs the reader how an innocent looking digital
image hides a deadly terrorist plan, which can
destroy the world just in a click of a mouse. It also
describes and discusses the process of secret
communication known as steganography. The
crucial argument here is that terrorists are most
likely to be employing digital steganography to
facilitate secret intra-group communication as has
been claimed. This is mainly because the use of
digital steganography by terrorist is both technically
and operationally dubious. The most important part
this paper discusses is that terrorist are likely to
employ low-tech steganography such as semagrams
and null chippers instead. It investigates the
strengths of image steganography and the reasons
why terrorists are relying on it so much.

Governments and companies are turning to automated tools to make sense of what people
post on social media, for everything ranging from hate speech detection to law enforcement
investigations. Policymakers routinely call for social media companies to identify and take
down hate speech, terrorist propaganda, harassment, “fake news” or disinformation, and
other forms of problematic speech. Other policy proposals have focused on mining social
media to inform law enforcement and immigration decisions. But these proposals wrongly
assume that automated technology can accomplish on a large scale the kind of nuanced
analysis that humans can accomplish on a small scale.

Social media platforms have recently seen an increase in the occurrence of hate speech discourse which has led to calls for improved detection methods. Most of these rely on annotated data, keywords, and a classification technique. While this approach provides good coverage, it can fall short when dealing with new terms produced by online extremist communities which act as original sources of words which have alternate hate speech meanings. These code words (which can be both created and adopted words) are designed to evade automatic detection and often have benign meanings in regular discourse. As an example, “skypes”, “googles”, and “yahoos” are all instances of words which have an alternate meaning that can be used for hate speech. This overlap introduces additional challenges when relying on keywords for both the collection of data that is specific to hate speech, and downstream classification. In this work, we develop a community detection approach for finding extremist hate speech communities and collecting data from their members. We also develop a word embedding model that learns the alternate hate speech meaning of words and demonstrate the candidacy of our code words with several annotation experiments, designed to determine if it is possible to recognize a word as being used for hate speech without knowing its alternate meaning. We report an inter-annotator agreement rate of K=0.871, and K=0.676 for data drawn from our extremist community and the keyword approach respectively, supporting our claim that hate speech detection is a contextual task and does not depend on a fixed list of keywords. Our goal is to advance the domain by providing a high quality hate speech dataset in addition to learned code words that can be fed into existing classification approaches, thus improving the accuracy of automated detection.