Manipulation During the French Presidential Campaign: Coordinated Inauthentic Behaviors and Astroturfing Analysis on Text and Images

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Complex Networks and Their Applications XI (COMPLEX NETWORKS 2016 2022)

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Abstract

In April 2022, the French presidential election took place, and social media played a prominent role in it. By analyzing more than 150 million interactions on French Twitter, this study aims to provide evidence of coordinated behaviors from political parties. We find that extreme parties left and right, appear with a particular internal structure compared to moderate parties. Moreover, by examining similar patterns in community structures but also in duplicated tweets, we unveil online astroturfing strategies of the main parties online, and in particular the extreme right.

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Acknowledgement

We would like to express our very great appreciation to Emily S. Cheng and Jeanne Bruneau–Bongard for their valuable and constructive suggestions during the writing of this research work. We would also like to thank reviewers for taking the time and effort necessary to review the manuscript and appreciate their valuable comments and suggestions for the discussion.

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Correspondence to Victor Chomel .

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Appendix

Appendix

Fig. 9.
figure 9

Example of repeatedly posted images within two narratives : the proximity of Marine Le Pen and Putin and the violence of the French police, especially during the Yellow Jackets movement

Fig. 10.
figure 10

Most posted images during the two weeks before the first round (left), between the two rounds (right). The first one is a manipulation of the Macron political campaign poster, with a caption about the McKinsey scandal. The second one is part of Macron’s campaign against Le Pen.

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Chomel, V., Panahi, M., Chavalarias, D. (2023). Manipulation During the French Presidential Campaign: Coordinated Inauthentic Behaviors and Astroturfing Analysis on Text and Images. In: Cherifi, H., Mantegna, R.N., Rocha, L.M., Cherifi, C., Miccichè, S. (eds) Complex Networks and Their Applications XI. COMPLEX NETWORKS 2016 2022. Studies in Computational Intelligence, vol 1077. Springer, Cham. https://doi.org/10.1007/978-3-031-21127-0_11

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  • DOI: https://doi.org/10.1007/978-3-031-21127-0_11

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