New generation sequencing evidenced that soil houses a huge microbial biodiversity. Based on these observations, it is now possible to better describe the spatial distribution of soil microbial communities, to study the ecological processes involved (environmental selection, dispersal limitations), and to compute the data to define the ecological attributes of soil microbial taxa. These huge datasets also offer the opportunity to study how soil microbial populations are interrelated. With this study, we revealed the first soil bacterial "social" network across French national territory based on 2,200 soils sampled in the French Soil Quality Monitoring Network. To characterize how bacterial taxa are related to one-another, the bacterial community composition was characterized using 454-pyrosequencing based on 16S rRNA genes directly amplified from soil DNA and bacterial taxa were identified based on SILVA database. Then, a co-occurrence network analysis was computed to visualize and quantify the network structure and complexity according to the combination of environmental parameters (soil, climate, land use). The results demonstrate that the soil bacterial network is highly complex at the scale of France with more positive relationships than negative. Comparing environmental conditions, the network was more complex in forest soil than in cropland or grassland when those of vineyards/orchards are drastically less complex. Beyond the global network structure, the relationships of each specific taxon changed across the land-use systems, implying both switch of partner, modify the kind or the number of relationships. Understanding these microbial networks represents a cornerstone of soil microbial ecology to go further in investigating ecological processes shaping soil microbial communities and to predict the impact of land-use on soil microbial diversity, and functioning.