Yazar
Duman, Ekrem
Basım Tarihi
2023
Basım Yeri
-
IOS Press
Konu
Banking, CRM, NLP, Sentiment analysis, Social media
Tür
Süreli Yayın
Dil
İngilizce
Dijital
Evet
Yazma
Hayır
Kütüphane
Özyeğin Üniversitesi
Demirbaş Numarası
1064-1246
Kayıt Numarası
b05cde10-d506-4e06-85ce-287a378905c2
Lokasyon
Industrial Engineering
Tarih
2023
Örnek Metin
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
