Analyzing User Experience in Mobile Banking Applications Through Text Mining

This study attempts to offer a data-driven comprehension of the factors that influence satisfaction and dissatisfaction by examining user reviews, based on a banking mobile application in Albania, specifically the Raiffeisen Bank application. All gathered reviews from Google Play and the App Store have been classified using the multilingual BERT model. It is important to mention that mBERT is particularly suitable given that the reviews are written in both Albanian and English. BERTopic has been used to determine the main topics of classification. After classifying the reviews and creating new dimensions with BERTopic, an ordinal logistic regression model was applied to the generated dataset to assess the predictive power of these dimensions and sentiment polarity on user-assigned satisfaction ratings. This study helps developers and managers to better understand the main factors that influence customer reactions and evaluate the factors that influence the rate of the application and the different bugs they report.

@article{(Myrto)2026,
  title     = {Analyzing User Experience in Mobile Banking Applications Through Text Mining},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {17},
  number    = {6},
  year      = {2026},
  publisher = {The Science and Information Organization},
  author    = {Bora Lamaj (Myrto) and Markela Muça and Klodiana Bani},
  doi       = {10.14569/IJACSA.2026.0170611},
  url       = {https://doi.org/10.14569/IJACSA.2026.0170611}
}