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Comparing Classification Trees to Discern Patterns of Terrorism.
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- المؤلفون: Saiya, Nilay1 ; Scime, Anthony2
- المصدر:
Social Science Quarterly (Wiley-Blackwell). Jun2019, Vol. 100 Issue 4, p1420-1444. 25p. 1 Diagram, 3 Charts.
- الموضوع:
- معلومة اضافية
- نبذة مختصرة :
Objective: Though applied widely in the fields of medicine, finance, ecology, psychology, and computer science, machine learning algorithmic‐based methods are a relatively novel approach to social scientific analysis that have yet to be extensively applied. Yet as we argue in this article, a specific form of algorithmic analysis known as C4.5 classification trees has much to offer social analysis and, specifically, the study of social and political violence. Method: This article describes four novel classification model comparison techniques for the C4.5 classification method and applies them to the study of terrorism. Results: Our state‐level analysis suggests that there is something fundamentally different in the targeting choices of religious and secular terrorists. Conclusion: This analysis highlights the ability of classification trees to heighten our understanding of terrorism and even provide recommendations to policymakers for avoiding future attacks. [ABSTRACT FROM AUTHOR]
- نبذة مختصرة :
Copyright of Social Science Quarterly (Wiley-Blackwell) is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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