social apprehension of the Yellow Vest which is no longer cacophonic but polyphonic, taken in a dynamic of interacting narratives and counter narratives. This interaction is particularly obvious when the journalistic framework oscillates between a political and social reading and an episodic reading of a movement that disrupts the journalistic and political fields. Moreover, this social apprehension also reflects a collective in the process of being formed which knows how to use digitals lever to increase its visibility.

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This paper studies how academic content published in Open Edition.org, an online publication platform in the Social Sciences and Humanities is re-appropriated by members of the public. Our research is therefore concerned with the public appropriation of science and Open science. After extracting the contexts of citation of these content and mapping them, we propose a typology of citation functions as well as of citers (their origins and types). Our preliminary results indicated that academic literature is repurposed and cited by members of the public mainly as scientific warrant (support for their argumentation). We also found that academic content is cited in all types of web documents including blogs, press releases, book reviews, newspaper articles, scientific articles, discussion forums, library catalogs, government agencies or ministries. Finally, we looked at that the elapsed time between the publication of an academic content and its citation in the public arena and found that this follows the already observed citations patterns within the scientific community (sleeping beauties, long tail, unexpected reader, silent conversation).

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La place croissante des réseaux sociaux numériques dans le débat public amène les chercheurs et journalistes à investiguer ces matériaux. Si l’apport des sciences sociales est indéniable dans la compréhension des mouvements sociaux actuels, les chercheurs en sciences humaines et sociales, dans leur ensemble, ne sont que peu formés à ces matériaux. Au fur et à mesure des besoins, des outils de recueil et de traitement de données ont vu le jour, et permettent aujourd’hui de manipuler et d’extraire les données sans compétences techniques particulières. Mais cette aisance des interfaces masque une complexité de manipulation de données, ou des choix ont été opérés indépendamment d’une recherche précise. Notre article propose de présenter ces divers éléments et reprend pour l’analyse de données issues de Twitter les choix d’extraction, d’analyse de réseaux et d’analyse lexicales.