BackgroundDigital spaces, and in particular social networking sites, are becoming increasingly present and influential in the functioning of our democracies. In this paper, we propose an integrated methodology for the data collection, the reconstruction, the analysis and the visualization of the development of a country’s political landscape from Twitter data.MethodThe proposed method relies solely on the interactions between Twitter accounts and is independent of the characteristics of the shared contents such as the language of the tweets. We validate our methodology on a case study on the 2017 French presidential election (60 million Twitter exchanges between more than 2.4 million users) via two independent methods: the comparison between our automated political categorization and a human categorization based on the evaluation of a sample of 5000 profiles descriptions; the correspondence between the reconfigurations detected in the reconstructed political landscape and key political events reported in the media. This latter validation demonstrated the ability of our approach to accurately reflect the reconfigurations at play in the off-line political scene.ResultsWe built on this reconstruction to give insights into the opinion dynamics and the reconfigurations of political communities at play during a presidential election. First, we propose a quantitative description and analysis of the political engagement of members of political communities. Second, we analyze the impact of political communities on information diffusion and in particular on their role in the fake news phenomena. We measure a differential echo chamber effect on the different types of political news (fake news, debunks, standard news) caused by the community structure and emphasize the importance of addressing the meso-structures of political networks in understanding the fake news phenomena.ConclusionsGiving access to an intermediate level, between sociological surveys in the field and large statistical studies (such as those conducted by national or international organizations) we demonstrate that social networks data make it possible to qualify and quantify the activity of political communities in a multi-polar political environment; as well as their temporal evolution and reconfiguration, their structure, their alliance strategies and their semantic particularities during a presidential campaign through the analysis of their digital traces. We conclude this paper with a comment on the political and ethical implications of the use of social networks data in politics. We stress the importance of developing social macroscopes that will enable citizens to better understand how they collectively make society and propose as example the “Politoscope”, a macroscope that delivers some of our results in an interactive way.

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.

Un candidat dispose au moins de trois leviers pour gagner les voix des électeurs : convaincre de la pertinence de son programme et de ses idées (positive campaigning), convaincre de l'inadéquation ou du danger des programmes et des idées de ses adversaires (negative campaigning), et enfin, rendre familier son nom et celui de son parti en les martelant auprès du public. Alors que nous assistons à une profonde transformation de l'articulation entre les partis politiques, leurs militants et leurs sympathisants, de quelle manière les personnalités politiques font-elles usage de ces leviers lors d'une campagne telle que la présidentielle et comment leurs communautés politiques contribuent-elles à les actionner ? Dans cet article, nous nous appuyons sur les données et la catégorisation des communautés politiques sur Twitter de Gaumont et al. (2018) pour aborder cette question du point de vue des réseaux sociaux. Nous proposons un ensemble de mesures quantitatives à différentes échelles pour qualifier les processus à l'oeuvre au sein des communautés politiques que nous avons suivies sur Twitter au cours de la présidentielle française de 2017. Nous montrons que les différentes communautés ont des manières distinctes de s'articuler avec les stratégies leur leader, pointant une hétérogénéité dans les formes de « division du travail » militant. Nous montrons également que les variations dans les stratégies des communautés peuvent aider à identifier les faiblesses temporaires ou la perte de confiance dans le leader ainsi que la position structurelle des candidats dans l'arène politique, ce qui nous permet d'identifier une anomalie dans l'attitude des politiciens à l'égard de la candidature de Marine Le Pen. Les figures de l'article peuvent être consultées dans une version interactive à cette adresse: http://reseaux.politoscope.org