MINING THE GAPS: A Text Mining-Based Meta-Analysis of the Current State of Research on Violent Extremism
abstract
This working paper presents the preliminary results of the RESOLVE Network Secretariat’s meta-analysis on the state of the research literature on violent extremism. The second in a series of working papers that takes stock of existing research in the field of preventing and countering violent extremism (P/CVE), this report examines large-scale patterns in P/CVE research. Using automated text-mining analysis tools, the authors and their teams collected and reviewed over 3,000 peer-reviewed English-language research articles and synthesized a number of findings to guide future P/CVE research efforts. The first of its kind to employ automated machine-learning analytical techniques to review literature on the intersection
between conflict, political violence, and anti-pluralist belief systems, the study revealed a number of critical gaps in existing research on violent extremism. A topic and term that is widely contested among policymakers, practitioners, and researchers alike, violent extremism defies attempts to define its conceptual boundaries. The analytical tools applied for this research, however, revealed important central threads that with further research might provide a pathway to a more cohesive analytical taxonomy of this highly complex, multifaceted field of research.