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These data are part of NACJD's Fast Track Release and are distributed as they were received from the data depositor. The files have been zipped by NACJD for release, but not checked or processed except for the removal of direct identifiers. Users should refer to the accompanying readme file for a brief description of the files available with this collection and consult the investigator(s) if further information is needed.

The study aimed to develop and empirically test a dynamic risk assessment model of radicalization process characteristics of homegrown terrorists inspired by Al Qaeda's ideology. The New York Police Department (NYPD) model developed by Mitchell D. Silber and Arvin Bhatt was chosen as the basis for creating a typology of overt and detectable indicators of individual behaviors widely thought to be associated with extremism. Specific behavioral cues associated with each stage of radicalization were coded and used to estimate the sequencing of behaviors and the duration of the average radicalization trajectory. Out of 331 homegrown American Jihadists (Group A), 135 were selected for further examination of their radicalization (Group B). Data were collected from public records ranging from social media postings by the offenders themselves to evidence introduced in the adjudication of the offenses for which the offenders were incarcerated. Life histories were compiled for Group B, whose detailed biographies were used to chart the timelines of their radicalization trajectories.

The collection includes an Excel file which contains one data table for Group A (10 variables, n=331) and two data tables for Group B (32 variables, n=135 and 5 variables, n=135, respectively). An accompanying codebook file details the variables in these tables. There is also a document with approximately 1 page narratives for each of the 135 individuals in Group B. A file containing a key indicating the names of the subjects is not available with this collection.

This project examines the trajectory of radicalization of jihadists and Incels with two broad objectives in mind. First, to develop new integrated computational technology that can mine, monitor, and screen for the occurrence of behaviors associated with dangerously escalating extremism in large heterogenous databases and provide early warnings of individuals or groups on behavioral trajectories toward extremist violence. Second, to harness data science methodologies to enable rapid, semi-automated support for law enforcement analysts and social science researchers to produce structured behavioral indicator profiles from text sources.

The study operated from the premise that being that violent extremists are a rare, complex phenomenon, it is futile to search for a profile of extremism. Rather, it is better to focus on explaining how people come to embrace violent extremism. This path, referred to here as a radicalization trajectory, implies that an arc exists leading the perpetrator from entertaining extremist ideas to action, and that there is a somewhat predictable pathway from a normal, if perhaps angry state, to the perpetration of a violent attack in the name of the ideology. Two teams were combined to analyze radicalization trajectories: data collection and analysis led by Brandeis University and technology development led by Colorado State University (CSU).

The questions revolving around the technological development were as follows: Can tools that rigorously examine and account for the activities of close associates better predict the likelihood that an individual would engage in violent extremism? Which risk assessment indicators for violent extremism in the extant literature are detectable via automated or semi-automated technologies, and what databases and datasets must be integrated to facilitate this detection? Can computationally efficient tools be used to mine these databases for the specific purposes of monitoring and screening for individuals and small groups posing a significant risk for violence?

Users should refer to the data collection notes field below for additional information about study citation.

This study compiled data on American jihadists and other Islamic extremists recruited since the early 1990s. Specifically, "homegrown" terrorist, referring to Americans and other Westerners who are inspired to commit acts of terrorism or support those committing these acts in their home country on behalf of foreign terrorist organizations, are the main focus. The purpose of this research is to address the central question: How do foreign terrorist organizations mobilize Americans to carry out attacks on their behalf?

Variables collected include extremist group affiliation, criminal background, foreign fighter history if applicable, coconspirators and their relationship, and the location and nature of terrorist plots. Demographic variables include sex, ethnicity, immigration status, education, and profession.