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. 2023;217(1-2):113-121.
doi: 10.1051/jbio/2023017. Epub 2023 Jul 6.

[Memories of the 13-November 2015 terrorist attacks: what discourse analysis can teach us]

[Article in French]
Denis Peschanski  1 , Bénédicte Pincemin  2 , Serge Heiden  3 , Charlotte Lacoste  4
Affiliations

[Memories of the 13-November 2015 terrorist attacks: what discourse analysis can teach us]

[Article in French]
Denis Peschanski et al. Biol Aujourdhui. 2023.

Abstract
in English, French

The Programme 13-Novembre aims to analyze the individual and collective memory of the terrorist attacks of November 13, 2015. At its heart is the Étude 1000, which is to gather the same 1000 people in audiovisual interviews four times in 10 years. Having the transcripts at our disposal, we choose here to show the importance of discourse analysis by recalling its theoretical foundations, to present one of the tools allowing this statistical analysis, the Correspondence Factor Analysis, and to use it to analyze the sub-corpus of interviews conducted at a distance from the Paris events, with 76 inhabitants of the Metz region. Crossing these volunteers with the words they use, we see that two variables clearly stand out that oppose the vocabularies, the gender variable and the age variable.

Title: Mémoires des attentats terroristes du 13-Novembre 2015 : ce que peut nous apprendre l’analyse de discours.

Abstract: Le Programme 13-Novembre vise à analyser la mémoire individuelle et collective des attentats terroristes du 13 novembre 2015. Au cœur se trouve l’Étude 1000 qui doit recueillir, à 4 reprises en 10 ans, les témoignages des mêmes 1000 personnes dans des entretiens audiovisuels. Disposant des transcriptions, nous choisissons ici de montrer l’importance de l’analyse de discours en rappelant ses fondements théoriques, de présenter l’un des outils permettant cette analyse statistique, l’Analyse Factorielle des Correspondances, et de l’utiliser pour analyser le sous-corpus des entretiens réalisés à distance des événements parisiens, auprès de 76 habitants de la région de Metz. Croisant ces volontaires avec les mots qu’ils utilisent, on constate que deux variables ressortent clairement qui opposent les vocabulaires, la variable du genre et la variable de l’âge.

Keywords: Analyse Factorielle des Correspondances; Correspondence Analysis; collective memory; individual memory; memory sciences; mémoire collective; mémoire individuelle; sciences de la mémoire; textometry; textométrie.

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