Toward a computational history of universities: Evaluating text mining methods for interdisciplinarity detection from PhD dissertation abstracts.

For the first time, historians of higher education have large data sets of primary sources that reflect the complete output of academic institutions at their disposal. To analyze this unprecedented abundance of digital materials, scholars have access to a large suite of computational methods develop...

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Detalles Bibliográficos

Publicado en:	Digital Scholarship in the Humanities Vol. 33; no. 3; pp. 612 - 621
Autores principales:	Nanni, Federico, Dietz, Laura, Ponzetto, Simone Paolo
Formato:	Artículo
Publicado:	Oxford University Press / USA Sep2018
Materias:	Text mining Interdisciplinary education Academic dissertations Natural language processing Big data
Acceso en línea:	Ver este registro en EBSCOhost