Online Library

A counter-intuitive finding emerges from an analysis of Arabic Twitter posts from 2014 to 2015: Twitter participants who are negative toward the Islamic State of Iraq and the Levant (ISIS) are also more likely to hold negative views of the United States. This surprising correlation is due to the interpretations of two sets of users. One set of users views the United States and ISIS negatively as independent interventionist powers in the region. The other set of users negatively links the United States with ISIS, often asserting a secretive conspiracy between the two. The intense negativity toward the United States in the Middle East seems conducive to views that, in one way or another, cause citizens to link the United States and ISIS in a conspiratorial manner.

A partir de un análisis de publicaciones en árabe en Twitter correspondientes al período 2014–2015, surge una conclusión contraria a la intuición: Quienes participan en Twitter y tienen una actitud negativa con respecto al Estado Islámico de Irak y el Levante (EIIL) también tienen más probabilidades de ostentar una opinión negativa con respecto a los Estados Unidos (EE. UU.). Esta sorprendente correlación se debe a las interpretaciones de dos grupos de usuarios. Uno de dichos grupos tiene una visión negativa de los EE. UU. y del EIIL, ya que los considera poderes intervencionistas independientes en la región. El otro grupo de usuarios establece una vinculación negativa entre los EE. UU. y el EIIL, y suele afirmar que existe una conspiración secreta entre los dos. La intensa negatividad con respecto a los Estados Unidos en el Oriente Medio parece propiciar opiniones que, de una u otra manera, hacen que los ciudadanos establezcan una vinculación conspirativa entre los EE. UU. y el EIIL.

Une conclusion contre-intuitive ressort d’une analyse des publications Twitter en arabe de 2014–2015: les participants à Twitter qui ont une opinion négative de l’État islamique en Irak et au Levant sont également plus susceptibles d’avoir une opinion négative des États-Unis. Cette corrélation surprenante est due aux interprétations de deux ensembles d’utilisateurs. Un ensemble d’utilisateurs voit négativement les États-Unis et l’État islamique en Irak et au Levant puisqu’il les considère comme des puissances interventionnistes indépendantes dans la région. L’autre ensemble d’utilisateurs les associe négativement en affirmant souvent qu’il existe une conspiration secrète entre eux deux. L’intense négativité à l’égard des États-Unis au Moyen-Orient semble propice à des points de vue qui, d’une manière ou d’une autre, amènent les citoyens à établir un lien conspirationniste entre les États-Unis et l’État islamique en Irak et au Levant.

Young people – politicised, active and highly connected – are no longer just passive consumers of online terrorist content by adult groomers but are themselves propaganda creators, group organisers, peer recruiters, extremist financers and terrorist convicts. This process, called “youth‑on‑youth radicalisation”, emphasises the agency that young people have in a digital era in which the information hierarchy is increasingly flattened. Noting the formation of several new young extreme‑right groups and a series of terrorist convictions across Western Europe, this paper takes first steps to investigate the specific nature of this emerging threat.

What is the relationship between the words and deeds of a terrorist group? Despite frequent speculation in media and policy circles, few studies have tested this relationship. This study aims to verify a potential correlation between the volume of propaganda produced by Islamic State (IS)—including statements by the group’s leadership—and the number of attacks carried out in its name. We examine this issue by comparing two datasets: one of all official propaganda produced by the Islamic State in 2016, and another of the completed, failed, and disrupted plots carried out by the group and its supporters in Europe in the same year. We find no strong and predictable correlation between the volume of propaganda Islamic State produces and the number of attacks the group and its supporters carry out. There is no regular rise in IS propaganda output before or after its attacks. In particular, there is no regular rise in attacks after leadership statements. However, the results may have identified differences in how IS central and regional media offices respond to attacks. The findings suggest that rather than merely looking at the volume of IS propaganda, it is necessary to also examine its content. As such, the deliberately broad premise of this study is intended as the first in a series of papers examining the potential relationship between IS propaganda and IS attacks.

In recent decades, information technology went through an explosive evolution, revolutionizing the way communication takes place, on the one hand enabling the rapid, easy and almost costless digital interaction, but, on the other, easing the adoption of more aggressive communication styles. It is crucial to regulate and attenuate these behaviors, especially in the digital context, where these emerge at a fast and uncontrollable pace and often cause severe damage to the targets. Social networks and other entities tend to channel their efforts into minimizing hate speech, but the way each one handles the issue varies. Thus, in this thesis, we investigate the problem of hate speech detection in social networks, focusing directly on Twitter. Our first goal was to conduct a systematic literature review of the topic, targeting mostly theoretical and practical approaches. We exhaustively collected and critically summarized mostly recent literature addressing the topic, highlighting popular definitions of hate, common targets and different manifestations of such behaviors. Most perspectives tackle the problem by adopting machine learning approaches, focusing mostly on text mining and natural language processing techniques, on Twitter. Other authors present novel features addressing the users themselves. Although most recent approaches target Twitter, we noticed there were few tools available that would address this social network platform or tweets in particular, considering their informal and specific syntax. Thus, our second goal was to develop a tokenizer able to split tweets into their corresponding tokens, taking into account all their particularities. We performed two binary hate identification experiments, having achieved the best f-score in one of them using our tokenizer. We used our tool in the experiments conducted in the following chapters. As our third goal, we proposed to assess which text-based features and preprocessing techniques would produce the best results in hate speech detection. During our literature review, we collected the most common preprocessing, sentiment and vectorization features and extracted the ones we found suitable for Twitter in particular. We concluded that preprocessing the data is crucial to reduce its dimensionality, which is often a problem in small datasets. Additionally, the f-score also improved. Furthermore, analyzing the tweets’ semantics and extracting their character n-grams were the tested features that better improved the detection of hate, enhancing the f-score by 1.5% and the hate recall by almost 5% on unseen testing data. On the other hand, analyzing the tweets’ sentiment didn’t prove to be helpful. Our final goal derived from a lack of user-based features in the literature. Thus, we investigated a set of features based on profiling Twitter users, focusing on several aspects, such as the gender of authors and mentioned users, their tendency towards hateful behaviors and other characteristics related to their accounts (e.g. number of friends and followers). For each user, we also generated an ego network, and computed graph-related statistics (e.g. centrality, homophily), achieving significant improvements – f-score and hate recall increased by 5.7% and 7%, respectively.

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 activated 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 proISIS
terms through Twitter.

While the internet provides access to rich educational experiences, great entertainment, and the chance to connect with friends around the clock, it also creates a number of risks that young people, parents, and guardians need to be aware of. There are the commonly known concerns of identity theft, online predators, and cyber-bullying but there is another issue that we need to collectively work to address— Radicalisation to violence. This informational resource strives to increase the awareness of how the internet is being used to radicalise and recruit youth in North America.