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It is now commonplace to observe that we are facing a deluge of onlineinformation. Researchers have of course long acknowledged the potential valueof this information since digital traces make it possible to directly observe,describe and analyze social facts, and above all the co-evolution of ideas andcommunities over time. However, most online information is expressed throughtext, which means it is not directly usable by machines, since computersrequire structured, organized and typed information in order to be able tomanipulate it. Our goal is thus twofold: 1. Provide new natural languageprocessing techniques aiming at automatically extracting relevant informationfrom texts, especially in the context of social sciences, and connect thesepieces of information so as to obtain relevant socio-semantic networks; 2.Provide new ways of exploring these socio-semantic networks, thanks to toolsallowing one to dynamically navigate these networks, de-construct andre-construct them interactively, from different points of view following theneeds expressed by domain experts.

Generating Navigable Semantic Maps from Social Sciences Corpora