Text is a basic material, a primary data layer, in many areas of humanities and social sciences. If we want to move forward with the agenda that the fields of digital humanities and computational social sciences are projecting, it is vital to bring together the technical areas that deal with automated text processing, and scholars in the humanities and social sciences. Much progress has been made in the last two decades in text analytics, a field that draws on recent advances in computational linguistics, information retrieval and machine learning. By now we know what to expect from basic tools, such as named entity recognition. To foster new areas of research, it is necessary to not only understand what is out there in terms of proven technologies and infrastructures such as CLARIN, but also how the developers of text analytics can work with researchers in the humanities and social sciences to understand the challenges in each other’s field better. What are the research questions of the researchers working on the texts? Can answering these questions be supported by computational models (in a non-reductionistic way)?

The LDK tutorial took place on 18 June 2017, as part of the preconference programme for LDK 2017, the conference on Language, Data and Knowledge that took place on 19-20 June 2017 in Galway, Ireland. The tutorial is co-organized by CLARIN and DARIAH-Ireland.