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. Lately, the Islamic State of Iraq and Syria (ISIS) has managed to control large parts of Syria and Iraq. To better understand the roots of support for ISIS, we present a study using Twitter data. We collected a large number of Arabic tweets referring to ISIS and classified them as pro-ISIS or anti-ISIS. We then analyzed the historical timelines of both user groups and looked at their pre-ISIS period to gain insights into the antecedents of support. Also, we built a classifier to ‘predict’, in retrospect, who will support or oppose the group. We show that ISIS supporters largely differ from ISIS opposition in that the former referred a lot more to Arab Spring uprisings that failed than the latter. The computer science research community has became increasingly interested in the study of social media due to their pervasiveness in the everyday life of millions of individuals. Methodological questions and technical challenges abound as more and more data from social platforms become available for analysis. This data deluge not only yields the unprecedented opportunity to unravel questions about online individuals' behavior at scale, but also allows to explore the potential perils that the massive adoption of social media brings to our society. These communication channels provide plenty of incentives (both economical and social) and opportunities for abuse. As social media activity became increasingly intertwined with the events in the offline world, individuals and organizations have found ways to exploit these platforms to spread misinformation, to attack and smear others, or to deceive and manipulate. During crises, social media have been effectively used for emergency response, but fear-mongering actions have also triggered mass hysteria and panic. Criminal gangs and terrorist organizations like ISIS adopt social media for propaganda and recruitment. Synthetic activity and social bots have been used to coordinate orchestrated astroturf campaigns, to manipulate political elections and the stock market. The lack of effective content verification systems on many of these platforms, including Twitter and Facebook, rises concerns when younger users become exposed to cyber-bulling, harassment, or hate speech, inducing risks like depression and suicide. This article illustrates some of the recent advances facing these issues and discusses what it remains to be done, including the challenges to address in the future to make social media a more useful and accessible, safer and healthier environment for all users. The Isis toolkit offers the sophisticated capabilities required to analyze digital personas and provide investigators with clues to the identity of the individual or group hiding behind one or more personas. To assess sympathetic variability in chronic heart failure (CHF), we evaluated a distribution of inter-spike intervals (ISIs) in renal sympathetic nerve activity (RSNA) in salt-sensitive hypertension-induced CHF (DSSH-CHF) rats. Dahl salt-sensitive rats were fed an 8 NaCl diet for 9 weeks to induce salt-sensitive hypertension-induced CHF. ISIs in RSNA were obtained from chronically instrumented conscious rats, and counts (frequency) and ranks of ISIs in RSNA were plotted with a histogram. We found that ISIs in RSNA followed a power-law distribution in rats, and the power-law distribution of ISIs for RSNA in DSSH-CHF rats was significantly different from that in normal rats. These results indicated that sympathetic variability may be significantly different between salt-sensitive hypertension-induced CHF and healthy individuals, which suggests that sympathetic variability may be used to predict abnormality of the sympathetic regulatory system. The Islamic State of Iraq and al-Sham (ISIS) is a dominant insurgent group operating in Iraq and Syria that rose to prominence when it took over Mosul in June, 2014. In this paper, we present a data-driven approach to analyzing this group using a dataset consisting of 2200 incidents of military activity surrounding ISIS and the forces that oppose it (including Iraqi, Syrian, and the American-led coalition). We combine ideas from logic programming and causal reasoning to mine for association rules for which we present evidence of causality. We present relationships that link ISIS vehicle-bourne improvised explosive device (VBIED) activity in Syria with military operations in Iraq, coalition air strikes, and ISIS IED activity, as well as rules that may serve as indicators of spikes in indirect fire, suicide attacks, and arrests. Science has traditionally been mapped on the basis of authorship and citation data. Due to publication and citation delays such data represents the structure of science as it existed in the past. We propose to map science by proxy of journal relationships derived from usage data to determine research trends as they presently occur. This mapping is performed by applying a principal components analysis superimposed with a k-means cluster analysis on networks of journal relationships derived from a large set of article usage data collected for the Los Alamos National Laboratory research community. Results indicate that meaningful maps of the interests of a local scientific community can be derived from usage data. Subject groupings in the mappings corresponds to Thomson ISI subject categories. A comparison to maps resulting from the analysis of 2003 Thomson ISI Journal Citation Report data reveals interesting differences between the features of local usage and global citation data. In the 24 hours prior to her death by suicide, a young girl made 145 posts on Twitter. In the posts, she outlines her history of incestuous sexual abuse, rape, and risky sexual behavior. These posts were analyzed using the Linguistic Inquiry and Word Count (LIWC). Trends were found indicating an increase in positive emotions over the 24 hours and a change in focus from the self to others. This first study of posts on Twitter by a person about to commit suicide provides hypotheses for future studies of this medium for communication. The discrete-time Gaussian channel with intersymbol interference (ISI) where the inputs are subject to a per symbol average-energy constraint is considered. The capacity of this channel is derived by means of a hypothetical channel model called the N-circular Gaussian channel (NCGC), whose capacity is readily derived using the theory of the discrete Fourier transform. The results obtained for the NCGC are used further to prove that, in the limit of increasing block length N, the capacity of the discrete-time Gaussian channel (DTGC) with ISI using a per block average-energy input constraint (N-block DTGC) is indeed also the capacity when using the per symbol average-energy constraint. > Scholars are increasingly citing electronic “web references” which are not preserved in libraries or full text archives. WebCite is a new standard for citing web references. To “webcite” a document involves archiving the cited Web page through www.webcitation.org and citing the WebCite permalink instead of (or in addition to) the unstable live Web page. This journal has amended its “instructions for authors” accordingly, asking authors to archive cited Web pages before submitting a manuscript. Almost 200 other journals are already using the system. We discuss the rationale for WebCite, its technology, and how scholars, editors, and publishers can benefit from the service. Citing scholars initiate an archiving process of all cited Web references, ideally before they submit a manuscript. Authors of online documents and websites which are expected to be cited by others can ensure that their work is permanently available by creating an archived copy using WebCite and providing the citation information including the WebCite link on their Web document(s). Editors should ask their authors to cache all cited Web addresses (Uniform Resource Locators, or URLs) “prospectively” before submitting their manuscripts to their journal. Editors and publishers should also instruct their copyeditors to cache cited Web material if the author has not done so already. Finally, WebCite can process publisher submitted “citing articles” (submitted for example as eXtensible Markup Language [XML] documents) to automatically archive all cited Web pages shortly before or on publication. Finally, WebCite can act as a focussed crawler, caching retrospectively references of already published articles. Copyright issues are addressed by honouring respective Internet standards (robot exclusion files, no-cache and no-archive tags). Long-term preservation is ensured by agreements with libraries and digital preservation organizations. The resulting WebCite Index may also have applications for research assessment exercises, being able to measure the impact of Web services and published Web documents through access and Web citation metrics. @PARASPLIT [J Med Internet Res 2005;7(5):e60] The problem of blind demodulation of multiuser information symbols in a high-rate code-division multiple-access (CDMA) network in the presence of both multiple-access interference (MAI) and intersymbol interference (ISI) is considered. The dispersive CDMA channel is first cast into a multiple-input multiple-output (MIMO) signal model framework. By applying the theory of blind MIMO channel identification and equalization, it is then shown that under certain conditions the multiuser information symbols can be recovered without any prior knowledge of the channel or the users' signature waveforms (including the desired user's signature waveform), although the algorithmic complexity of such an approach is prohibitively high. However, in practice, the signature waveform of the user of interest is always available at the receiver. It is shown that by incorporating this knowledge, the impulse response of each user's dispersive channel can be identified using a subspace method. It is further shown that based on the identified signal subspace parameters and the channel response, two linear detectors that are capable of suppressing both MAI and ISI, i.e., a zero-forcing detector and a minimum-mean-square-error (MMSE) detector, can be constructed in closed form, at almost no extra computational cost. Data detection can then be furnished by applying these linear detectors (obtained blindly) to the received signal. The major contribution of this paper is the development of these subspace-based blind techniques for joint suppression of MAI and ISI in the dispersive CDMA channels. With the widespread use of email, we now have access to unprecedented amounts of text that we ourselves have written. In this paper, we show how sentiment analysis can be used in tandem with effective visualizations to quantify and track emotions in many types of mail. We create a large word--emotion association lexicon by crowdsourcing, and use it to compare emotions in love letters, hate mail, and suicide notes. We show that there are marked differences across genders in how they use emotion words in work-place email. For example, women use many words from the joy--sadness axis, whereas men prefer terms from the fear--trust axis. Finally, we show visualizations that can help people track emotions in their emails. Personal weblogs (blogs), provide individuals with the opportunity to write freely and express themselves online in the presence of others. In such situations, what do bloggers write about, and what are their motivations for blogging? Using a large blog corpus annotated with the LIWC text analysis program, we examine the content of blogs to provide insight into the role of personality in motivation for blogging. As predicted, we find that highly Neurotic authors use blogs to serve a cathartic or auto-therapeutic function, and reflect mainly upon themselves and negative emotions. Highly Extraverted blog authors, as expected, use blogs to document their lives at a high level, and uniquely interact directly with the reader. Additionally Extraverts use blogs to vent both positive and negative emotions. Bloggers who are high scorers on the Openness trait are more concerned with leisure activities, although they are more evaluative than intellectual, whereas high Conscientiousness bloggers tend to report daily life – and work – around them. As in other contexts, expressing positive rather than negative emotions is associated with high Agreeableness, but that trait is associated with self reference to a greater degree in blogs than elsewhere. In general, findings are consistent with other contexts indicating that bloggers tend to adapt to the possibilities of the medium, rather than try to present themselves differently. Individuals communicate and form relationships through Internet social networking websites such as Facebook and MySpace. We study risk taking, trust, and privacy concerns with regard to social networking websites among 205 college students using both reliable scales and behavior. Individuals with profiles on social networking websites have greater risk taking attitudes than those who do not; greater risk taking attitudes exist among men than women. Facebook has a greater sense of trust than MySpace. General privacy concerns and identity information disclosure concerns are of greater concern to women than men. Greater percentages of men than women display their phone numbers and home addresses on social networking websites. Social networking websites should inform potential users that risk taking and privacy concerns are potentially relevant and important concerns before individuals sign-up and create social networking websites. Author(s): Aldous, DJ | Abstract: Consider N particles, which merge into clusters according to the following rule: a cluster of size x and a cluster of size y merge at (stochastic) rate K(x, y) N, were AT is a specified rate kernel. This Marcus-Lushnikov model of stochastic coalescence and the underlying deterministic approximation given by the Smoluchowski coagulation equations have an extensive scientific literature. Some mathematical literature (Kingman's coalescent in population genetics; component sizes in random graphs) implicitly studies the special cases K(x, y) = 1 and K(x, y) = xy. We attempt a wide-ranging survey. General kernels are only now starting to be studied rigorously; so many interesting open problems appear. © 1999 ISI BS. In the Molecular Communication (MC), molecules are utilized to encode, transmit, and receive information. Transmission of the information is achieved by means of diffusion of molecules and the information is recovered based on the molecule concentration variations at the receiver location. The MC is very prone to intersymbol interference (ISI) due to residual molecules emitted previously. Furthermore, the stochastic nature of the molecule movements adds noise to the MC. For the first time, we propose four methods for a receiver in the MC to recover the transmitted information distorted by both ISI and noise. We introduce sequence detection methods based on maximum a posteriori (MAP) and maximum likelihood (ML) criterions, a linear equalizer based on minimum mean-square error (MMSE) criterion, and a decision-feedback equalizer (DFE) which is a nonlinear equalizer. We present a channel estimator to estimate time varying MC channel at the receiver. The performances of the proposed methods based on bit error rates are evaluated. The sequence detection methods reveal the best performance at the expense of computational complexity. However, the MMSE equalizer has the lowest performance with the lowest computational complexity. The results show that using these methods significantly increases the information transmission rate in the MC. A new form of document coupling called co-citation is defined as the frequency with which two documents are cited together. The co-citation frequency of two scientific papers can be determined by comparing lists of citing documents in the Science Citation Index and counting identical entries. Networks of co-cited papers can be generated for specific scientific specialties, and an example is drawn from the literature of particle physics. Co-citation patterns are found to differ significantly from bibliographic coupling patterns, but to agree generally with patterns of direct citation. Clusters of co-cited papers provide a new way to study the specialty structure of science. They may provide a new approach to indexing and to the creation of SDI profiles. A content analysis of the ABC News Online website during the 2000 Olympic Games reveals a select few female role models were available to young audiences. One female athlete was 'news-privileged'. Cathy Freeman's exposure came at the expense of her Australian team mates, especially those women who won medals in team sports. While the results indicate an improvement in both the extent of women's sports coverage and the range of sports covered, stereotypical descriptions often characterised adult females as emotionally vulnerable, dependent adolescents. Male athletes were never infantilised and were far less likely to be described in emotive terms. Recent years have witnessed the explosive growth of online social media. Weibo, a Twitter-like online social network in China, has attracted more than 300 million users in less than three years, with more than 1000 tweets generated in every second. These tweets not only convey the factual information, but also reflect the emotional states of the authors, which are very important for understanding user behaviors. However, a tweet in Weibo is extremely short and the words it contains evolve extraordinarily fast. Moreover, the Chinese corpus of sentiments is still very small, which prevents the conventional keyword-based methods from being used. In light of this, we build a system called MoodLens, which to our best knowledge is the first system for sentiment analysis of Chinese tweets in Weibo. In MoodLens, 95 emoticons are mapped into four categories of sentiments, i.e. angry, disgusting, joyful, and sad, which serve as the class labels of tweets. We then collect over 3.5 million labeled tweets as the corpus and train a fast Naive Bayes classifier, with an empirical precision of 64.3 . MoodLens also implements an incremental learning method to tackle the problem of the sentiment shift and the generation of new words. Using MoodLens for real-time tweets obtained from Weibo, several interesting temporal and spatial patterns are observed. Also, sentiment variations are well captured by MoodLens to effectively detect abnormal events in China. Finally, by using the highly efficient Naive Bayes classifier, MoodLens is capable of online real-time sentiment monitoring. The demo of MoodLens can be found at http: goo.gl 8DQ65.