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Sentence-Based Text Analysis for Customer Reviews


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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


Link zum Volltext (externe URL): http://pubsonline.informs.org/doi/10.1287/mksc.201...


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

Schlagwörter:extended LDA model; user-generated content; text data; unstructured data; Bayesian analysis; big data
Institutionen der Universität:Wirtschaftswissenschaftliche Fakultät > Betriebswirtschaftslehre > Lehrstuhl für Allgemeine Betriebswirtschaftslehre, Absatzwirtschaft und Marketing
DOI / URN / ID:10.1287/mksc.2016.0993
Titel an der KU entstanden:Ja
Eingestellt am:16. Aug 2017 10:50
Letzte Änderung:16. Aug 2017 10:50
URL zu dieser Anzeige:http://edoc.ku-eichstaett.de/20301/