Computational Reception and Readership Studies

  • van Dalen-Oskam, K. H. (Speaker)
  • Karl Berglund (Speaker)
  • Melanie Walsh (Speaker)
  • Angelina Eimannsberger (Speaker)

Activity: Talk or presentationAcademic


Panel. The ongoing digitalization is affecting all aspects of the book trade: production, distribution, consumption, reception. Besides its direct impact, this systemic shift also changes publishing studies and contemporary book history: When reading and reception is increasingly turning into digital activities, reading and reception becomes digital data. And these data points can be studied computationally. In fact, and in line with Lev Manovich, among others, computational approaches are necessary to grasp our digital culture due to the mere scale of these datasets.
This panel argues that data points deriving from digital platforms seem to be one of the more promising operationalizations of reception and reading that publishing studies and book history have ever had access to. Furthermore, the best way to understand these platforms is by investigating them on their own terms. This, however, by no means rules out an uncritical, uninformed or positivist approach to the results found. There is no conflict between computational methods and a critical perspective based on contextual knowledge
The panel will highlight and discuss the relevance and need for computational approaches in contemporary book history when it comes to studying reception and readership. It will 1) provide critical discussions on computational methodologies for contemporary book history, their strengths and weaknesses and how they most fruitfully are to be combined with qualitative approaches; and 2) showcase empirical studies of important digital arenas for reception (e.g. Goodreads) and reading (e.g. Storytel), based on but not limited to computational work.
Period13 Jul 2022
Event titleSHARP 2022: Power of the written word
Event typeConference
LocationAmsterdam, NetherlandsShow on map
Degree of RecognitionInternational


  • computational analysis
  • reader research