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Background: Digital 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. Method: The 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. Results: We 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. Conclusions: Giving 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. [ABSTRACT FROM AUTHOR]

Background: Migrants account for 35% of HIV diagnoses in the European Union (ECDC/WHO 2014). Little is known about the impact of such a lifelong infection diagnosis on lives that are already disrupted by migration. In this paper, we assess the impact of HIV diagnosis on activity, union, well-being among African migrants living in France, the second group most affected by HIV after MSM. We compare it with the impact of the diagnosis of Hepatitis B, another lifelong infection affecting African migrants. Methods: We use the ANRS PARCOURS survey, a retrospective life-event survey led in 2012–2013 in 74 health structures in Paris greater area which collected 926 life histories of Sub-Saharan migrants living with HIV and 779 with Hepatitis B. We modelled the probability year by year since 18 years of age until data collection to lose one’s activity, to experience a conjugal break up and degradation of well-being and we estimated the impact of migration and of HIV and Hepatitis B diagnoses on these probabilities, after adjustment on other factors, thanks to discrete-time logistic regressions. Results: Migration entailed loss of activity and conjugal break up, though HIV diagnosis after migration did not statistically impact on these outcomes. Yet HIV diagnosis had a massive negative impact on well-being (aOR = 11.31 [4.64–27.56] for men and 5.75 [2.79–11.86] for women). This negative impact on well-being tended to diminish for persons diagnosed after 2004. The negative impact of HIV diagnosis on African migrants’ well-being seems to be attenuated in the last decade, which hints at a normalization of the subjective experience of HIV diagnosis. [ABSTRACT FROM AUTHOR]