Extending monitoring methods to textual data: a research agenda

Triss Ashton (), Nicholas Evangelopoulos () and Victor Prybutok ()

Quality & Quantity: International Journal of Methodology, 2014, vol. 48, issue 4, 2277-2294

Abstract: Textual data has become increasingly common in business analytic data sets. While concept-based text mining offers a method of extracting meaningful information from text data, methods for monitoring of customer perceptions of business processes and products that are discussed in customer-generated documents are not immediately available. We explore the results of two text-mining algorithms and review issues observed in the data that affect uploading the results onto a newly proposed methodological monitoring platform analogous to statistical process control charts. Finally, we discuss several topics for future research in text mining. Copyright Springer Science+Business Media Dordrecht 2014

Keywords: Latent semantic analysis; Latent Dirichlet allocation; Process monitoring; Control charts (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s11135-013-9891-8

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