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Natural language processing (NLP) has become a fieldof interest for many researchers within the humanities. However, framing humanities research questions as NLP problems and identifying suitable methods can be a difficult task. Taking previous and ongoing projects from the Centre for Digital Humanities and Social Sciences at Uppsala University (CDHU) as a point of departure, this chapter presents concrete use cases of how humanities research questions can be approached using various NLP methods and tools, from ready-to-use text analysis tools to programming libraries that require basic familiarity with Python. Two case studies from the field of history and literature will be introduced to illuminate how texts can be processed for humanities research purposes. With this chapter, we hope to give the reader the means to directly explore NLP methods for their research as well as encourage further learning.

This invited perspective is a response to the position paper “The Right to Read Without Being Read: Research Ethics in the Study of Digital Reading Behaviour”. From the point of view of the researcher behind one of the case studies discussed in the position paper, this paper highlights three perspectives on research ethics: 1) the potential negative effects for individuals of studying book streaming data as in the project design are minimal, and ethics have been discussed continuously in the project; 2) the question whether this kind of data is to be considered sensitive data or not is not simple, and it is important to restrict this label to data that is indeed sensitive; and 3) questions concerning privacy evoked by this kind of reader data are recurrently addressed in the research by the author.