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Current research that seeks to inform terrorism prevention, intervention, and interdiction efforts has been hampered by at least three problems: the lack of adequate control groups, a tendency to conceptually conflate radicalization with mobilization, and a preponderance of research designs that only include data on the perpetrator or the event, but not both. This project addresses these shortcomings by collecting data that includes control groups consisting of non-violent offenders, non-mobilized ideologues, and unsuccessful terrorists, and by modeling mobilization as the interaction between individual characteristics, social networks, and event-level situational opportunities for action. The integrated approach of this research isolates the interactive factors that distinguish violent from nonviolent offenders, identifies the individual, network, and event-level variables that are significantly related to extremist mobilization, and determines which law enforcement interdiction strategies are most likely to succeed in stopping terrorist attacks.

This research expands on the NIJ-funded Profiles of Individual Radicalization in the United States (PIRUS) and Social Networks of American Radicals (SoNAR) datasets to include event-level information on more than 1,400 United States-based extremist plots and financial crimes from 1974-2021. These event data can be linked to data on the individuals and networks contained in the PIRUS and SoNAR datasets, respectively, in order to build a fully relational database on radicalization characteristics, social-network dynamics, and event-level details and outcomes. Data collection used open-sources, including media reports, unsealed court documents, unclassified government reports, and other open-source archived content. To strengthen the reliability and validity of the analyses, at least 25% of the data were double coded, and the project team dedicated the last phase of data collection to conduct rigorous quality control. To analyze these data, the project team used three methods: descriptive and bivariate analyses, advanced regression methods with regularization, and multi-step configurational methods on a subset of 50 event cases.

These data are currently available as an Excel workbook. The "Plots" sheet contains data on premeditated violent and non-violent crimes. The "Financial Crimes" sheet contains data on financial crimes only. Please refer to the ICPSR README for more information.

This project sought to improve understanding of the characteristics of bias crime in the United States by collecting and analyzing data on a national sample of offenders. The database - The Bias Incidents and Actors Study (BIAS) - includes information on 966 adult offenders who committed hate crimes in the United States from 1990-2018. BIAS includes offenders who committed crimes that were motivated by bias based on (1) race, ethnicity, or ancestry; (2) religion; (3) sexual orientation, gender, or gender identity; (4) disability; and (5) age. BIAS includes more than 100 variable fields that cover all aspects of an offender's background, including their demographic characteristics, family dynamics, education and employment histories, mental health concerns, criminal records, peer associations, and hate group affiliations. BIAS also include details on the nature of the offender's crime, such as whether it was violent or non-violent, spontaneous or premeditated, or was perpetrated alone, with a group, or while under the influence of drugs and alcohol.

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 Empirical Assessment of Domestic Radicalization (EADR) project seeks to provide practitioners, researchers, and the public with an empirical foundation for understanding the radicalization processes of United States-based extremists. Project researchers utilized a mixed-method, nested approach to explore a number of key research questions related to radicalization, including:

• what are the demographic, background, and radicalization differences between and within the different ideological milieus?
• are there important contextual, personal, ideological, or experiential differences between radicals who commit violent acts and those who do not?
• is it possible to identify sufficient pathways to violent extremism?
• are the causal mechanisms highlighted by extant theories of radicalization supported by empirical evidence?

The collection includes 5 SPSS datasets and 2 SPSS syntax files:

• PIRUS_full_dataset_ICPSR_archive.sav (n=1,473; 113 variables)
• PIRUS_expected_maximization_version.sav (n=16,203; 27 variables)
• PIRUS_fixed_value_imputation_version.sav (n=1,473; 27 variables)
• PIRUS_regression_based_imputation_version.sav (n=16,203; 28 variables)
• PIRUS_subgroup_mean_substitution_version.sav (n=1,473; 27 variables)
• quantitative_analysis_syntax.sps
• variable_prep_syntax.sps