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Foreword-The standard media image of violent extremism may seem to be far from the ordinary work of the Swedish Media Council. While extremism is often described in dramatic terms of terrorism, attacks and riots, the Council’s work concerns more everyday things, such as age limits for cinema films and media awareness teaching in pre-school. But no person is born to be a perpetrator of violence for political or religious purposes. Being recruited to and radicalised within the framework of pro-violence
and anti-democratic extremist groups is a question of adopting, more or less uncritically, an image of the world where hate is the driving force and violence the legitimate means. In today’s information society, the Internet has become, to an ever increasing extent, the tool for spreading anti-democratic messages for the purpose of recruiting new members. This fact places great demands on people young and old to retain a critical view of information and sometime sharply angled messages that we come across in both traditional and digital media. In October 2011, the Government mandated the Swedish Media Council to describe the presence of anti-democratic messages on the Internet and in social media. The focus is on messages aimed at young persons, and that encourage violence for political or ideological reasons. The aim is to create broader knowledge about extremist Internet milieu, their content, and how recruitment strategies
are formulated and communicated. The overall purpose is to strengthen young persons in preparation for encounters with such messages.

The capture of Mosul in the summer of 2014 by the self-styled ‘Islamic State’ appears today much more than a significant military event in the complex scenario of the Middle-East and in the tangled situation of Iraq and Syria. Close observers were not surprised. The establishment of the ‘Islamic State’ has characterized most of the recent history of this part of the world and has shown the ability to benefit from the inability to provide a clear answer to all the deep political and social unrest in this region. The symbol of this constant evolution and transformation is found in the various names that have been adopted over the years, from al-Qaeda in Iraq (AQI); Islamic State in Iraq (ISI); Islamic State in Iraq and the Levant (ISIL/ISIS); to the current Islamic State (IS). This aspect should not be overlooked.

Research surrounding radicalization to and use of violence among extremist and terror groups has expanded over the last decade. There are still fundamental questions that must be addressed, particularly regarding the role of the Internet in radicalisation and recruitment as well as general technological skill within extremist groups. Few studies have considered this issue, especially among Far Right groups which have been identified as one of the top threats to public safety within the United States. This exploratory study addresses these issues using a qualitative analysis of a sample of threads from a technology-specific subforum of a widely used web forum in the white nationalist and white power movement. The findings demonstrate that the process of information sharing is distinct from that of more sophisticated deviant and criminal communities on-line, as users readily answer basic technological questions rather than discuss offensive attack techniques. The implications of this study for future research are examined in depth.

The Arab Spring raised high expectations for political freedom, especially for situations in which the rapid development of ICT intersects with political oppression and rebellion, as was the case in Mali, West Africa. In 2012 the country’s northern part fell into the hands of ‘rebels’ and jihadists were on the rise. This article tries to understand the development of political agency in relation to the unprecedented access to new ICT of the Fulani nomads and urbanites in the Mopti region (Hayre), who engage increasingly with new actors and networks present in the war zone: ‘rebels’ and jihadists; the diaspora from that region; and the journalistic and academic communities who visit the region. We argue that political agency is emerging in the relation between (newly appearing) information networks in both the on- and off-line worlds. These networked societies are embedded in cultural and social historical specificities of the Sudan-Sahel zone in conflict.

Twitter is the largest and most popular micro-blogging website on Internet. Due to low publication barrier, anonymity and wide penetration, Twitter has become an easy target or platform for extremists to disseminate their ideologies and opinions by posting hate and extremism promoting tweets. Millions of tweets are posted on Twitter everyday and it is practically impossible for Twitter moderators or an intelligence and security analyst to manually identify such tweets, users and communities. However, automatic classification of tweets into pre-defined categories is a non-trivial problem problem due to short text of the tweet (the maximum length of a tweet can be 140 characters) and noisy content (incorrect grammar, spelling mistakes, presence of standard and non-standard abbreviations and slang). We frame the problem of hate and extremism promoting tweet detection as a one-class or unary-class categorization problem by learning a statistical model from a training set containing only the objects of one class . We propose several linguistic features such as presence of war, religious, negative emotions and offensive terms to discriminate hate and extremism promoting tweets from other tweets. We employ a single-class SVM and KNN algorithm for one-class classification task. We conduct a case-study on Jihad, perform a characterization study of the tweets and measure the precision and recall of the machine-learning based classifier. Experimental results on large and real-world dataset demonstrate that the proposed approach is effective with F-score of 0.60 and 0.83 for the KNN and SVM classifier respectively.

Security informatics and intelligence computation plays a vital role in detecting and classifying terrorism contents in the web. Accurate web content classification using the computational intelligence and security informatics will increase the opportunities of the early detection of the potential terrorist activities. In this paper, we propose a modified frequency-based term weighting scheme for accurate Dark Web content classification. The proposed term weighting scheme is compared to the common techniques used in text classification such as Term Frequency (TF), Term Frequency-Inverse Document Frequency (TF-IFD), and Term Frequency- Relative Frequency (tf.rf), on a dataset selected from Dark Web Portal Forum. The experimental results show that the classification accuracy and other evaluation measures based on the proposed scheme outperforms other term weighting techniques based classification.