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The Future of Bangla Sentiment Analysis: Advancements, Challenges, and Opportunities for Practical and Research Innovation

Year: 2025

Type: article

Abstract: Bangla sentiment analysis has advanced significantly, transitioning from rule-based models and lexicons to deep learning and transformer-based architectures. Despite these developments, the field still faces critical challenges, including limited labeled data, complex morphology, code-mixed language, and dialectal variation. Although recent models and datasets have improved accuracy, key issues remain such as narrow domain coverage, underexplored aspect-based and emotion classification, and potential ethical concerns related to bias and fairness. This paper critically examines current approaches, including deep neural and cross-lingual models, and highlights new frontiers like multimodal sentiment analysis and real-time inference. It also outlines strategic directions for future research, focusing on zero-shot learning, dialogue-based sentiment detection, and fairness-aware frameworks. The study aims to provide a roadmap for making Bangla sentiment analysis both technologically robust and socially responsible.

Source: Journal of Information System and Technology Management

DOI: 10.35631/jistm.1039002

Authors: Md Riaz Hasan, Fariha Sultana, Harun Or Rashid, Lahmidi Rida

Institutions: Southeast University, Hohai University, Nanjing University of Science and Technology

Language: English

Topic: Sentiment Analysis and Opinion Mining

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: diamond

Funders: Nanjing University of Science and Technology, Nanjing University, Southeast University, Hohai University

OpenAlex ID: W4412675589

FWCI: 1.281

Cites:

Cited by: 3

Related to: 10