How to Analyse Non-Digital Historical Archives of Large Organizations — A Text-Mining Case Study

WST Working Paper Series

34 Pages Posted: 22 Dec 2019

Date Written: September 26, 2019

Abstract

In modern case study-based research projects, the emerging technological possibilities of computer-aided content analysis are becoming increasingly prominent. Especially in the fields of sociology, history and management and organization sciences (MOS), the amount of available data is constantly increasing, which complicates or limits manual analysis. Emerging techniques open up possibilities for analysis, and they need to be explored. In a research project on a large, non-digital archive of a large utility company, we tried several approaches to digitally analyse the documents. Through this task, we identified the possibilities and limits of digital analysis. In this paper, we present these with a case study and give other researchers concrete solutions for use in comparable projects, including the digitization, interpretation and visualization of results.

Keywords: text mining, digital text analysis, big data analysis, archival research, archival documents, case studies, digitization, data cleaning

JEL Classification: C80, C88, N01, Y20

Suggested Citation

Reiter, Brian-Patrick, How to Analyse Non-Digital Historical Archives of Large Organizations — A Text-Mining Case Study (September 26, 2019). WST Working Paper Series, Available at SSRN: https://ssrn.com/abstract=3460121 or http://dx.doi.org/10.2139/ssrn.3460121

Brian-Patrick Reiter (Contact Author)

RWTH Aachen University ( email )

Templergraben 55
Aachen, 52062
Germany

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