Linkages as a lens: An exploration of strategic communications in P/CVE.

Strategic communications for the purpose of countering violent extremism have become widespread in recent years, especially given the communications revolution which has amplified the messages of violent extremists and those that wish to counter them. Despite this, there is little-to-no research which collects message data and analyses its design in a systematic way. In this article, we collect data from 10 social media multi-message campaigns and undertake an exploratory analysis of their design using a methodology developed from Ingram’s “Linkage-based” framework for countering militant Islamist propaganda. Our findings include: a prevalence towards highlighting the atrocities of violent extremist groups rather than strategies which challenge their competence; a priority to messages which seize the narrative agenda; differing emotional or rational pulls depending on the language in which the message is delivered; a range of different tactics employed depending on the target audience; as well as a wide range of deployments of different themes of positive and negative messages. We offer a number of possible explanations for these findings, before undertaking a cluster analysis of the data to aid the construction of Weberian “ideal type” campaigns, which offer a contribution to the field for the purposes of future research and exposition

An empirical study of PLAD regression using the bootstrap

Partial LAD regression uses the L 1 norm associated with least absolute deviations (LAD) regression while retaining the same algorithmic structure of univariate partial least squares (PLS) regression. We use the bootstrap in order to assess the partial LAD regression model performance and to make comparisons to PLS regression. We use a variety of examples coming from NIR experiments as well as two sets of experimental dat

Linkages as a Lens: An Exploration of Strategic Communications in P/CVE.

Strategic communications for the purpose of countering violent extremism have become widespread in recent years, especially given the communications revolution which has amplified the messages of violent extremists and those that wish to counter them. Despite this, there is little-to-no research which collects message data and analyses its design in a systematic way. In this article, we collect data from 10 social media multi-message campaigns and undertake an exploratory analysis of their design using a methodology developed from Ingram’s “Linkage-based” framework for countering militant Islamist propaganda. Our findings include: a prevalence towards highlighting the atrocities of violent extremist groups rather than strategies which challenge their competence; a priority to messages which seize the narrative agenda; differing emotional or rational pulls depending on the language in which the message is delivered; a range of different tactics employed depending on the target audience; as well as a wide range of deployments of different themes of positive and negative messages. We offer a number of possible explanations for these findings, before undertaking a cluster analysis of the data to aid the construction of Weberian “ideal type” campaigns, which offer a contribution to the field for the purposes of future research and exposition

Partial quantile regression

Partial least squares regression (PLSR) is a method of finding a reliable predictor of the response variable when there are more regressors than observations. It does so by eliciting a small number of components from the regressors that are inherently informative about the response. Quantile regression (QR) estimates the quantiles of the response distribution by regression functions of the covariates, and so gives a fuller description of the response than does the usual regression for the mean value of the response. We extend QR to partial quantile regression (PQR) when there are more regressors than observations. For each percentile the method provides a low dimensional approximation to the joint distribution of the covariates and response with a given coverage probability and which, under further linearity assumptions, estimates the corresponding quantile of the conditional distribution. The methodology parallels the procedure for PLSR using a quantile covariance that is appropriate for predicting a quantile rather than the usual covariance which is appropriate for predicting a mean value. The analysis suggests a new measure of risk associated with the quantile regressions. Examples are given that illustrate the methodology and the benefits accrued, based on simulated data and the analysis of spectrometer dat

Online Radicalization: Contested Terms and Conceptual Clarity

National governments and international governmental organisations have identified online radicalisation as one of today’s most pressing security challenges. It is thus unsurprising that there is a burgeoning literature on the topic. Within this literature, use of the terms “radicalisation”, “self-radicalisation”, “online radicalisation” and “echo chamber” is common. Also common is the tendency for those who use these terms to assume that their meanings are self-evident. In this chapter we seek to show that this is not in fact the case. The chapter begins by explaining why conceptual clarity is important. It then examines each of the four terms in turn, showing that, even though the terms can be – and indeed are – understood in different ways, there is a tendency to assume that there is a shared understanding of what each term means. The chapter explains the problems to which this lack of conceptual clarity gives rise and concludes by suggesting some directions for future research that will advance understanding of the role the internet plays in contemporary violent extremism

Protocol for steroid radioimmunoassay of plasma

This protocol can be used to measure the concentration of steroid hormones in small plasma samples. This protocol has been copied and modified from protocols provided by Dr. John Wingfield at the University of Washington. It has been written for use in the laboratory of Dr. Ellen Ketterson at Indiana University, and therefore the details may require modification if the procedure is performed elsewhere. The general procedure, which takes 4-5 days to complete, is described below. Prepared January 1998 by Joe Casto, modified December 2005 by Jodie Jawor and May 2010 by Danielle Whittaker

Recommender systems and the amplification of extremist content

Policymakers have recently expressed concerns over the role of recommendation algorithms and their role in forming “filter bubbles.” This is a particularly prescient concern in the context of extremist content online; these algorithms may promote extremist content at the expense of more moderate voices. In this article, we make two contributions to this debate. Firstly, we provide a novel empirical analysis of three platforms’ recommendation systems when interacting with far-right content. We find that one platform – YouTube – does amplify extreme and fringe content, while two – Reddit and Gab – do not. Secondly, we contextualise these findings into the regulatory debate. There are currently few policy instruments for dealing with algorithmic amplification, and those that do exist largely focus on transparency. We argue that policymakers have yet to fully understand the problems inherent in “de-amplifying” legal, borderline content and argue that a co-regulatory approach may offer a route towards tackling many of these challenges

Online Extremism and Terrorism Researchers’ Security, Safety, and Resilience:: Findings from the Field

This report presents findings from the REASSURE (Researcher, Security, Safety, and Resilience) project’s in-depth interviews with 39 online extremism and terrorism researchers. Based at universities, research institutes, and think tanks in Europe and North America, the interviewees studied mainly, albeit not exclusively, far-right and violent jihadist online activity. The report catalogues for the first time the range of harms they have experienced, the lack of formalised systems of care or training, and their reliance therefore on informal support networks to mitigate those harms