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2008 - ISPP 31st Annual Scientific Meeting Words: 247 words || 
1. Tournyol du Clos, Lorraine. "French terrorism : the clues of a descriptive analysis" Paper presented at the annual meeting of the ISPP 31st Annual Scientific Meeting, Sciences Po, Paris, France, <Not Available>. 2019-06-27 <>
Publication Type: Paper (prepared oral presentation)
Abstract: Using strength and terror to influence political decisions, terrorism weakens societal balance and leads to specific political responses. Conversely authorities implement policies that impact terrorist activity. These interactions between authorities and terrorism cannot be understood without an in-depth knowledge of actors’ strategies and operating modes. Descriptive statistics give concretely additive cases in the debate allowing political decision-makers to discover, confirm or measure existing interactions.

This presentation studies multifaceted French terrorism to show how much a simple descriptive approach (using GTD during the last 30 years of the 20th century) is able to enlighten knowledge on existing interactions between terrorism types and geographical areas, between terrorist groups, between terrorism and public policies. It provides a few clues as to reasons behind the mutations and threats France has been subjected to since then.

Using time series analysis methods, trends were created using simple descriptive statistics of terrorism over time and place. Through correlation analyses, we compare groups’ trends and geographical distribution over time. We also isolate monthly impacts by using a smoothing model with a moving average order of 12 to examine the seasonality of Corsican activity. By using Principal Component Factor Analysis (PCA) we highlight affinities between groups by crossing information regarding operating modes between the principal groups.

The results demonstrate that separatist violence is one of the keys themes in French terrorism and that it is highly geographically centralized. Chronologically, the Corsican, terrorist organizations showed trends in seasonality. The Principal Component Analysis (PCA) revealed interesting affinities among the groups.

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