Helsinki Computational History Group
Helsinki Computational History Group (COMHIS) is a multidisciplinary team that studies intellectual history. The work in the group is guided by methods from various different backgrounds ranging from modern data science and machine learning to history and linguistics. "Computational history" implies the use of mixed methods in which big data approach is combined to expert subject knowledge in intellectual history and book history.
The main research objective of the group is an integrated study of public discourse and knowledge production that combines metadata from library catalogues as well as full-text libraries of books, newspapers and periodicals in early modern Europe. The group implements this strategy through different projects and is currently involved, for example, in a Finnish consortium to study the development of public discourse in Finland and in an international H2020 project entitled the NewsEye. Of the various historical periods that these projects focus on, the eighteenth-century and the Enlightenment play a central role in the group’s work.
Metadata & collaboration
The core methodology of COMHIS research is shaped by open data analytical ecosystems. These provide transparent and reproducible approach...
Research & outputs
The main research objective of the group is an integrated study of public discourse and knowledge production that combines metadata from...
The group, led by PI Mikko Tolonen, takes valuable input and contributions from a wide group of people. The following people, in order of...
Computational History Group
Video introduction to COMHIS