Title: Analysing of online user reviews via latent Dirichlet allocation: Moroccan mobile banking case

Authors: Meriem Tabiaa; Abdellah Madani

Addresses: LAROSERI Laboratory, Computer Science Department, Chouaib Doukkali University, El Jadida, 24000, Morocco ' LAROSERI Laboratory, Computer Science Department, Chouaib Doukkali University, El Jadida, 24000, Morocco

Abstract: Nowadays, most organisations make their mobile applications available through different stores, such as Google Play Store, Apple App Store, and Windows Phone Store. Banks and financial institutions have also provided mobile applications for their customers. These app stores not only allow users to download applications but also to leave comments and reviews. In the present paper, we will first explore eight Moroccan mobile banking apps in the Google Play Store. Data that has not been exploited by Moroccan banks yet. Once the preprocessing phase is complete, we will examine and analyse user reviews using latent Dirichlet allocation (LDA) to extract and identify topics. Topics discovered focus mainly on security, services, quality and interface. While customer reviews can influence future demand, it may also be useful to decision-makers to improve their services and customer experience.

Keywords: latent Dirichlet allocation; LDA; topic model; e-banking; electronic banking; user reviews; consumer feedback.

DOI: 10.1504/IJBIS.2024.143872

International Journal of Business Information Systems, 2024 Vol.47 No.4, pp.480 - 494

Received: 24 Aug 2020
Accepted: 20 May 2021
Published online: 12 Jan 2025 *

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