The role of the internet in radicalization and recruitment processes has recently been the subject of much attention, discussion and debate. Such have downplayed the significance of the internet, arguing that traditional offline interactions play a more significant role in radicalization processes, although admitting that the internet acts as a ‘force multiplier’ or ‘radicalization accelerant’ (Sageman, 2004; Sageman, 2008; ICSR, 2009; RCMP, 2009). In a recent review of the state of the literature relating to criminological approaches to terrorism, Freilich et al (2015) identify the need to compare terror offenders with those who hold similar beliefs but have not committed any terrorism. Until now the trend has been to compare terrorists with other violent criminals, such as murderers. The need to compare terrorists with non-violent radicals should be intuitive. Both groups are exposed to the same types of information, materials and environments, they share certain core beliefs, outlooks and philosophies, and yet one group goes on to engage in violent acts while the other does not. Indeed, only a very small percentage of those who ascribe to extremist ideologies go on to be involved in terrorism, whether in supporting roles or by actually engaging in violence (Horgan, 2008; ICCT, 2016). There are also various levels of participation or involvement which can only be gauged on a case by case basis. Generally speaking, there are also many terrorists who have not strongly adhered to a radical ideology or been overly religious (Alarid, 2016), just as there are a great many adherents of radical ideology who have never engaged in terrorism. As such, the current study seeks to examine the differences in the NSM activity and behaviors of terrorists and non-violent radicals, specifically seeking to identify differences in online behavioral patterns, lexicon changes and network characteristics.
The current study uses Social Learning Theory, with an emphasis on the Differential Association processes in order to examine the key differences in NSM behaviors and activities. The study will employ experimental software provided by Terregence that offers a unique user interface for accessing the Facebook API and extracting user activities and page activities for open pages and profiles. The software also enables the automatic production of key trends and NSM metrics associated with these open pages and profiles. The software's abilities extend to conducting social network analysis and identification of lexical patterns and changes. This unique study seeks to shed light on the online predictors of online radicalization. While three distinct analyses will be conducted, this draft proposal presents the theoretical framework for only the first two of these analyses.