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Introducing the United States Extremis Crime Database (ECDB)
Abstract
This note describes a new and unique, open source, relational database called the United States Extremist Crime Database (ECDB). We first explain how the ECDB was created and outline its distinguishing features in terms of inclusion criteria and assessment of ideological commitment. Second, the article discusses issues related to the evaluation of the ECDB, such as reliability and selectivity. Third, descriptive results are provided to illustrate the contributions that the ECDB can make to research on terrorism and criminology.
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Citations
Cited by
Quest for Significance and Violent Extremism: The Case of Domestic Radicalization
Jasko, K., LaFree, G., & Kruglanski, A. (2017) · Political Psychology · doi:10.1111/pops.12376 · Cited by 258
The importance of influential users in (re)producing Swedish far-right discourse on Twitter
Åkerlund, M. (2020) · European Journal of Communication · doi:10.1177/0267323120940909 · Cited by 59
Metadata
- Authors
- Freilich, J. D., Chermak, S. M., Belli, R., Gruenewald, J., & Parkin, W. S.
- Venue
- Terrorism and Political Violence
- Publisher
- Informa UK Limited
- Published
- 2013-11-20
- Volume
- 26
- Issue
- 2
- Pages
- 372-384
- ISSN
- 0954-6553 (ISSN-L)
- 1556-1836
- OpenAlex
- W2036085599
- Cited by
- 161
- References
- 0
- FWCI
- 44.31
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Introducing the United States Extremis Crime Database (ECDB). https://app.cochat.ai/papers/10.1080/09546553.2012.713229
- The paper
- Freilich, J. D., Chermak, S. M., Belli, R., Gruenewald, J., & Parkin, W. S. (2014). Introducing the United States Extremis Crime Database (ECDB). Terrorism and Political Violence. https://doi.org/10.1080/09546553.2012.713229
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
