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Publication detail
FRIDRICH, M.
Original Title
Understanding customer churn prediction research with structural topic models
Type
journal article in Web of Science
Language
English
Original Abstract
Customer churn prediction is showing a growth in attention from both researchers and practitioners, creating a vast body of scientific works while being recognized as an indispensable tool of corporate retention activities. Thus, we aim to demonstrate the potential of structural topic models to navigate through the research articles and to identify essential themes and trends within the field of customer defection prediction. We apply a modified modeling procedure to journal articles focused on customer churn. As a result, the structural model of 38 topics is formed and examined considering topic prevalence, its changes over time, and the scientific impact (citations). We see prevailing themes tackling broad perspectives such as modeling, evaluation, and performance metrics. Furthermore, we recognize a slow decline in business & marketing aspects of churn prediction coupled with rising of more nuanced topics. At last, we discuss possible future steps in topic modeling within the domain.
Keywords
Customer Churn Prediction, Natural Language Processing, Topic Modeling
Authors
Released
14. 12. 2020
Publisher
Academy of Economic Studies in Bucharest
Location
Bucharest, Romania
ISBN
1842-3264
Periodical
Economic Computation and Economic Cybernetics Studies and Research
Year of study
54
Number
4
State
Romania
Pages from
301
Pages to
317
Pages count
16
URL
http://ecocyb.ase.ro/nr2020_4/19.+Martin+FRIDRICH+(T).pdf
BibTex
@article{BUT167274, author="Martin {Fridrich}", title="Understanding customer churn prediction research with structural topic models", journal="Economic Computation and Economic Cybernetics Studies and Research", year="2020", volume="54", number="4", pages="301--317", doi="10.24818/18423264/54.4.20.19", issn="1842-3264", url="http://ecocyb.ase.ro/nr2020_4/19.+Martin+FRIDRICH+(T).pdf" }