Text Mining for Information Systems Researchers: An Annotated Tutorial

S. Debortoli, O. Müller, I. Junglas, J. vom Brocke, Communications of the Association for Information Systems (2016) 555--582.

Download
No fulltext has been uploaded.
Journal Article
Author
; ; ;
Abstract
Analysts have estimated that more than 80 percent of today's data is stored in unstructured form (e.g., text, audio, image, video)—much of it expressed in rich and ambiguous natural language. Traditionally, to analyze natural language, one has used qualitative data-analysis approaches, such as manual coding. Yet, the size of text data sets obtained from the Internet makes manual analysis virtually impossible. In this tutorial, we discuss the challenges encountered when applying automated text-mining techniques in information systems research. In particular, we showcase how to use probabilistic topic modeling via Latent Dirichlet allocation, an unsupervised text-mining technique, with a LASSO multinomial logistic regression to explain user satisfaction with an IT artifact by automatically analyzing more than 12,000 online customer reviews. For fellow information systems researchers, this tutorial provides guidance for conducting text-mining studies on their own and for evaluating the quality of others.
Publishing Year
Journal Title
Communications of the Association for Information Systems
Page
555--582
ISSN
LibreCat-ID

Cite this

Debortoli S, Müller O, Junglas I, vom Brocke J. Text Mining for Information Systems Researchers: An Annotated Tutorial. Communications of the Association for Information Systems. 2016:555--582. doi:10.17705/1CAIS.03907
Debortoli, S., Müller, O., Junglas, I., & vom Brocke, J. (2016). Text Mining for Information Systems Researchers: An Annotated Tutorial. Communications of the Association for Information Systems, 555--582. https://doi.org/10.17705/1CAIS.03907
@article{Debortoli_Müller_Junglas_vom Brocke_2016, title={Text Mining for Information Systems Researchers: An Annotated Tutorial}, DOI={10.17705/1CAIS.03907}, journal={Communications of the Association for Information Systems}, author={Debortoli, Stefan and Müller, Oliver and Junglas, Iris and vom Brocke, Jan}, year={2016}, pages={555--582} }
Debortoli, Stefan, Oliver Müller, Iris Junglas, and Jan vom Brocke. “Text Mining for Information Systems Researchers: An Annotated Tutorial.” Communications of the Association for Information Systems, 2016, 555--582. https://doi.org/10.17705/1CAIS.03907.
S. Debortoli, O. Müller, I. Junglas, and J. vom Brocke, “Text Mining for Information Systems Researchers: An Annotated Tutorial,” Communications of the Association for Information Systems, pp. 555--582, 2016.
Debortoli, Stefan, et al. “Text Mining for Information Systems Researchers: An Annotated Tutorial.” Communications of the Association for Information Systems, 2016, pp. 555--582, doi:10.17705/1CAIS.03907.

Export

Marked Publications

Open Data LibreCat

Search this title in

Google Scholar
ISBN Search