Recent terrorist attacks carried out on behalf of ISIS on American and European soil by lone wolf attackers or sleeper cells remind us of the importance of understanding the dynamics of radicalization mediated by social media communication channels. In this paper, we shed light on the social media activity of a group of twenty-five thousand users whose association with ISIS online radical propaganda has been manually verified. By using a computational tool known as dynamical activity-connectivity maps, based on network and temporal activity patterns, we investigate the dynamics of social influence within ISIS supporters. We finally quantify the effectiveness of ISIS propaganda by determining the adoption of extremist content in the general population and draw a parallel between radical propaganda and epidemics spreading, highlighting that information broadcasters and influential ISIS supporters generate highly-infectious cascades of information contagion. Our findings will help generate effective countermeasures to combat the group and other forms of online extremism.
A few studies explored unconventional data sources: one interesting example is the work by Vergani and Bliuc @cite_55 that uses sentiment analysis (Linguistic Inquiry and Word Count @cite_25 ) to investigate how language evolved across the first 11 Issues of Dabiq, the flagship ISIS propaganda magazine. Their analysis offers some insights about ISIS radicalization motives, emotions and concerns. For example, the authors found that ISIS has become increasingly concerned with females, reflecting their need to attract women to create their utopia society, not revolving around warriors but around families. ISIS also seems to have increased the use of internet jargon, possibly to connect with the identities of young individuals online.
@cite_55 @cite_25
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In this article we investigate the evolution of ISIS by analysing the text contained in Dabiq, the official ISIS’ internet magazine in English. Specifically, we used a computerized text analysis pro-gram LIWC (Linguistic Inquiry and Word Count) to investigate the evolution of the language of the first 11 Issues of Dabiq. First, our analysis showed that affiliation seems to be an increasingly important psychological motive for the group. Secondly, ISIS has been increasingly using emotions, which are an important mobilizing factor in collective action literature, in a strategic manner. Thirdly, ISIS language presents an increasing concern with females. Last but not least, our analysis shows that ISIS has been increasingly using internet jargon (net-speak), which shows how the group tries to adapt itself to the internet environment and to connect with the identities of young individuals. ISIS is of particular concern as it seems to be more successful at recruiting foreign fighters than other jihadist groups (such as al-Qaeda). This aspect is difficult to quantify because reliable it is hard to access data about the exact number, demographics and affiliation of the foreign fighters who joined those organizations. Yet according to reports by the European Union there is a concerning increase in recruitment rates and patterns, with ISIS being more successful at recruiting young individuals from Western countries than any other jihadist group (Archick, Belkin, Blanchard, Hemud, & Mix, 2015). Scholars suggested that the majority of newly recruited jihadists prefer ISIS to other jihadist groups (Karmon, 2015; Klausen, 2015; Peresin, 2015; Peresin & Cervone, 2015; Turner, 2015)and journalists reported that existing members of al-Qaeda even abandoned the group to join ISIS (Dilanian, 2015; Miller, 2014). Moreover, a 2015 report from the International Centre for the Study of Radicalisation and Political Violence based at London King’s College stated that the number of jihadist foreign fighters in Syria The emergence and actions of the so-called Islamic State of Iraq and the Levant (ISIL ISIS) has received widespread news coverage across the World, largely due to their capture of large swathes of land across Syria and Iraq, and the publishing of execution and propaganda videos. Enticed by such material published on social media and attracted to the cause of ISIS, there have been numerous reports of individuals from European countries (the United Kingdom and France in particular) moving to Syria and joining ISIS. In this paper our aim to understand what happens to Europe-based Twitter users before, during, and after they exhibit pro-ISIS behaviour (i.e. using pro-ISIS terms, sharing content from pro-ISIS accounts), characterising such behaviour as radicalisation signals. We adopt a data-mining oriented approach to computationally determine time points of activation (i.e. when users begin to adopt pro-ISIS behaviour), characterise divergent behaviour (both lexically and socially), and quantify influence dynamics as pro-ISIS terms are adopted. Our findings show that: (i) of 154K users examined only 727 exhibited signs of pro-ISIS behaviour and the vast majority of those 727 users became with such behaviour during the summer of 2014 when ISIS shared many beheading videos online; (ii) users exhibit significant behaviour divergence around the time of their activation, and; (iii) social homophily has a strong bearing on the diffusion process of pro-ISIS terms through Twitter. The rise of social media such as blogs and social networks has fueled interest in sentiment analysis. With the proliferation of reviews, ratings, recommendations and other forms of online expression, online opinion has turned into a kind of virtual currency for businesses looking to market their products, identify new opportunities and manage their reputations, therefore many are now looking to the field of sentiment analysis. In this paper, we present a feature-based sentence level approach for Arabic sentiment analysis. Our approach is using Arabic idioms saying phrases lexicon as a key importance for improving the detection of the sentiment polarity in Arabic sentences as well as a number of novels and rich set of linguistically motivated features contextual Intensifiers, contextual Shifter and negation handling), syntactic features for conflicting phrases which enhance the sentiment classification accuracy. Furthermore, we introduce an automatic expandable wide coverage polarity lexicon of Arabic sentiment words. The lexicon is built with gold-standard sentiment words as a seed which is manually collected and annotated and it expands and detects the sentiment orientation automatically of new sentiment words using synset aggregation technique and free online Arabic lexicons and thesauruses. Our data focus on modern standard Arabic (MSA) and Egyptian dialectal Arabic tweets and microblogs (hotel reservation, product reviews, etc.). The experimental results using our resources and techniques with SVM classifier indicate high performance levels, with accuracies of over 95 . The increased online presence of jihadists has raised the possibility of individuals being radicalised via the Internet. To date, the study of violent radicalisation has focused on dedicated jihadist websites and forums. This may not be the ideal starting point for such research, as participants in these venues may be described as "already made-up minds". Crawling a global social networking platform, such as YouTube, on the other hand, has the potential to unearth content and interaction aimed at radicalisation of those with little or no apparent prior interest in violent jihadism. This research explores whether such an approach is indeed fruitful. We collected a large dataset from a group within YouTube that we identified as potentially having a radicalising agenda. We analysed this data using social network analysis and sentiment analysis tools, examining the topics discussed and what the sentiment polarity (positive or negative) is towards these topics. In particular, we focus on gender differences in this group of users, suggesting most extreme and less tolerant views among female users.