Sentiment Analysis in Low-Resource Bangla Text Using Active Learning

Haque, Md Afnan Ul; Rahman, Ashiqur; Hashem, M. M. A.

doi:10.1109/eict54103.2021.9733711

2021 5th International Conference on Electrical Information and Communication Technology (EICT) 2021

DOI: 10.1109/eict54103.2021.9733711

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Sentiment Analysis in Low-Resource Bangla Text Using Active Learning

Md Afnan Ul Haque

Ashiqur Rahman

M. M. A. Hashem

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2024

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Cited by 2 publications

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Active Learning Empowered Sentiment Analysis: An Approach for Optimizing Smartphone Customer’s Review Sentiment Classification

Abbas,

Boulila,

Driss

et al. 2024

IEEE Trans. Consumer Electron.

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Active Learning Empowered Sentiment Analysis: An Approach for Optimizing Smartphone Customer’s Review Sentiment Classification

Abbas,

Boulila,

Driss

et al. 2024

IEEE Trans. Consumer Electron.

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Hate speech detection in the Bengali language: a comprehensive survey

Al Maruf,

Abidin,

Haque

et al. 2024

J Big Data

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The detection of hate speech (HS) in online platforms has become extremely important for maintaining a safe and inclusive environment. While significant progress has been made in English-language HS detection, methods for detecting HS in other languages, such as Bengali, have not been explored much like English. In this survey, we outlined the key challenges specific to HS detection in Bengali, including the scarcity of labeled datasets, linguistic nuances, and contextual variations. We also examined different approaches and methodologies employed by researchers to address these challenges, including classical machine learning techniques, ensemble approaches, and more recent deep learning advancements. Furthermore, we explored the performance metrics used for evaluation, including the accuracy, precision, recall, receiver operating characteristic (ROC) curve, area under the ROC curve (AUC), sensitivity, specificity, and F1 score, providing insights into the effectiveness of the proposed models. Additionally, we identified the limitations and future directions of research in Bengali HS detection, highlighting the need for larger annotated datasets, cross-lingual transfer learning techniques, and the incorporation of contextual information to improve the detection accuracy. This survey provides a comprehensive overview of the current state-of-the-art HS detection methods used in Bengali text and serves as a valuable resource for researchers and practitioners interested in understanding the advancements, challenges, and opportunities in addressing HS in the Bengali language, ultimately assisting in the creation of reliable and effective online platform detection systems.

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Sentiment Analysis in Low-Resource Bangla Text Using Active Learning

Cited by 2 publications

References 12 publications

Active Learning Empowered Sentiment Analysis: An Approach for Optimizing Smartphone Customer’s Review Sentiment Classification

Active Learning Empowered Sentiment Analysis: An Approach for Optimizing Smartphone Customer’s Review Sentiment Classification

Hate speech detection in the Bengali language: a comprehensive survey

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