Garth Davies's research while affiliated with Simon Fraser University and other places

... It alleges that the so-called '(Jewish) global elites' purposefully control the influx of migrants and refugees to destroy and degrade the white or Western culture 10 . Furthermore, Scrivens (2022) reports anti-Jewish hate in their analysis, "[the Jews have used a very sinister form of eugenics for thousands of years to build an extraordinarily cunning race]" 11 . ...

... Berbers et al. 2015;Figoureux and Van Gorp 2020). A striking pattern identified in this body of research is that Islam and Muslims tend to be disproportionately regarded as associated with terrorism, whereas incidents with perpetrators associated with, e.g., the extreme right appear to receive less attention and to be less likely to be characterised as terrorism (Kearns, Betus, and Lemieux 2019;Powell 2018;Zdjelar and Davies 2021). ...

... Two reports into online activity in the US (Moonshot 2020b) and Canada (Moonshot 2020a) both found evidence to suggest that searches for white supremacist keywords increased after lockdowns were introduced. Similarly, Davies, Wu, and Frank (2021) found that traffic on rightwing extremist and involuntary celibate (Incel) forums showed a demonstrable increase in posting behaviours. ...

... Such being the case, no matter what anti-riot tactic is being used, if the very rank-and-file who are assigned and expected to enforce such tactics are not suitable for that purpose, then the operation is deemed to fail (Dawson and Davies 2018). Indeed, police knowledge, attitudes, and values, by and large, shape, if not define, to a great extent the police approach to such public order interventions. ...

... we have been part of this growing field of research at the international CyberCrime research Centre (iCCrC), situated in Simon fraser University's School of Criminology. 1 our work has ranged from identifying radical users in online discussion forums (e.g., Scrivens, Davies, & frank, 2017) to understanding terrorist organizations' online recruitment efforts on various online platforms (e.g., Davies et al., 2015), to evaluating linguistic patterns presented in the online magazines of terrorist groups (e.g., macnair & frank, 2018a, 2018b). these experiences have provided us with insights regarding the applicability of a specific set of machine learning techniques and research methods to conduct large-scale data analyses of extremist content online. 2 in what follows, we will first describe a customized web-crawler that was developed at the iCCrC for the purpose of collecting, classifying, and interpreting extremist content online and on a large scale. ...

... Moreover, our analysis also revealed less discussed threats, mainly the worry that social media might act as an easy pathway for illegal activities among adolescents who would not normally engage in them. The prevalence of inappropriate content on social media and its effects on the wellbeing of adolescents has been extensively studied (Goodyear et al., 2018;Smahel et al., 2020) and it is known that social media plays a significant role in the radicalization of youth (Kardaş and Özdemir, 2018;Gaudette et al., 2021). This study extends prior research by focusing also on how social media promotes "lesser" crimes, such as shoplifting, which has received relatively little attention in prior research. ...

... Just as it makes sense to have a unifying framework to enhance consistency in these areas, it makes sense to have a national framework to standardize the collection, storage, and presentation of use-of-force data. This is especially important because differences currently exist across jurisdictions in terms of what data are collected (e.g., draw and display of intervention options versus actual applications of force) and how they are collected (Kiedrowski et al. 2015;Davies et al. 2019;Wortley et al. 2021). ...

... Articles were included if they used machine learning to develop a predictive model that could be applied to addressing or preventing violent extremism. Therefore, articles were excluded if they focused on other aspects of artificial intelligence that did not result in the development of a predictive model, such as the development of Web crawlers [49]. Articles were also excluded if they were only peripherally related to violent extremism. ...

... Sentiment analysis software has become increasingly popular in this field because, as the amount of 'opinionated data' online grows exponentially, it offers a wide range of applications that can help address previously untapped and challenging research problems (see Liu 2012). Researchers, for example, have successfully used sentiment analysis to detect extreme language (e.g., Davidson et al. 2017), websites (e.g., Scrivens and Frank 2016) and users online (e.g., Scrivens et al. 2017), as well as to measure levels of online propaganda (e.g., Burnap et al. 2014) and cyberhate (e.g., Williams and Burnap 2015) following a terrorism incident, and to evaluate how radical discourse evolves over time online (e.g., Scrivens et al. 2018). Sentiment analysis has also been used to detect violent extremist language (e.g., Abbasi and Chen 2005) and users online (e.g., Kaati et al. 2016), as well as to measure levels of -or propensity towards -violent radicalization online (e.g. ...

... Data were collected by researchers external to the authors of this paper, using an automated web crawler, designed specifically for operation on the Dark Web (see Monk et al., 2018). Known as The Dark Crawler (TDC), this tool integrated a law enforcement hash value database, comprising 2.1 million MD5 image hash values. ...