Titelangaben
Büschken, Joachim ; Allenby, Greg M.:
Sentence-Based Text Analysis for Customer Reviews.
In: Marketing Science : the marketing journal of the Institute for Operations Research and the Management Sciences. 35 (2016) 6.
- S. 953-975.
ISSN 0732-2399 ; 1526-548x
Volltext
Link zum Volltext (externe URL): http://pubsonline.informs.org/doi/10.1287/mksc.201... |
Kurzfassung/Abstract
Firms collect an increasing amount of consumer feedback in the form of unstructured consumer reviews. These reviews contain text about consumer experiences with products and services that are different from surveys that query consumers for specific information. A challenge in analyzing unstructured consumer reviews is in making sense of the topics that are expressed in the words used to describe these experiences. We propose a new model for text analysis that makes use of the sentence structure contained in the reviews and show that it leads to improved inference and prediction of consumer ratings relative to existing models using data from www.expedia.com and www.we8there.com. Sentence-based topics are found to be more distinguished and coherent than those identified from a word-based analysis.
Weitere Angaben
Publikationsform: | Artikel |
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Schlagwörter: | extended LDA model; user-generated content; text data; unstructured data; Bayesian analysis; big data |
Institutionen der Universität: | Wirtschaftswissenschaftliche Fakultät > Betriebswirtschaftslehre > ABWL, Absatzwirtschaft und Marketing |
DOI / URN / ID: | 10.1287/mksc.2016.0993 |
Peer-Review-Journal: | Ja |
Verlag: | INFORMS |
Die Zeitschrift ist nachgewiesen in: | |
Titel an der KU entstanden: | Ja |
KU.edoc-ID: | 20301 |
Letzte Änderung: 16. Aug 2017 10:50
URL zu dieser Anzeige: https://edoc.ku.de/id/eprint/20301/