Author
Duman, Ekrem
Publication Date
2023
Publication Place
-
IOS Press
Subject
Banking, CRM, NLP, Sentiment analysis, Social media
Type
Periodical
Language
English
Digital
Yes
Manuscript
No
Library
Özyeğin University
Library Asset ID
1064-1246
Record ID
b05cde10-d506-4e06-85ce-287a378905c2
Library Location
Industrial Engineering
Date
2023
Sample Text
The use of the social media (SM) has become more and more widespread during the last two decades, the companies started looking for insights for how they can improve their businesses using the information accumulating therein. In this regard, it is possible to distinguish between two lines of research: those based on anonymous data and those based on customer specific data. Although obtaining customer specific SM data is a challenging task, analysis of such individual data can result in very useful insights. In this study we take up this path for the customers of a bank, analyze their tweets and develop three kinds of analytical models: clustering, sentiment analysis and product propensity. For the latter one, we also develop a version where, besides the text information, the structural information available in the bank databases are also used in the models. The result of the study is a considerably more efficient set of analytical CRM models.
DOI
10.3233/JIFS-221619
Cilt
44
