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A Multi-Model Approach to English-Bangla Sentiment Classification of Government Mobile Banking App Reviews

Md. Naim Molla, MMM Fahim, Md. Binyamin, MR Karim

Preprint · 2026 · preprint

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TL;DR

Multilingual sentiment classification of government mobile banking app reviews (English + Bangla). Benchmarks several architectures for monitoring public service quality through NLP.

Abstract

This study presents a multi-model approach for sentiment classification of user reviews of government mobile banking applications in Bangladesh, handling both English and Bangla language inputs. We benchmark several classification architectures on a curated review dataset and evaluate their performance across sentiment categories, with implications for public service improvement and digital governance monitoring.

NLPSentiment AnalysisBanglaMobile BankingLLMBangladesh

BibTeX 

@article{molla2026a,
  title   = {A Multi-Model Approach to English-Bangla Sentiment Classification of Government Mobile Banking App Reviews},
  author  = {Md. Naim Molla and MMM Fahim and Md. Binyamin and MR Karim},
  year    = {2026},
  journal = {Preprint},
  url     = {https://www.researchgate.net/publication/403866800},
}