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Fig 1.

Social media user distribution in Bangladesh (2023).

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Table 1.

Related publications along with boundaries.

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Fig 2.

Workflow of our proposed model.

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Fig 3.

Percentage of comments for each class.

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Fig 4.

Word cloud of dataset.

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Table 2.

Numeric features of the dataset.

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Fig 5.

Density plot of comments length before and after preprocessing the dataset.

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Fig 6.

Original and processed text of Bengali text dataset.

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Fig 7.

Example of CV & TF-IDF transformation representation of a comment.

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Fig 8.

Example of tokenization and padding representation of a comment.

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Fig 9.

Arrangement of the stacking ensemble.

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Fig 10.

Arrangement of the voting ensemble.

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Table 3.

ANOVA and chi2 tests results.

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Table 4.

Comparative overview of all DL and ML algorithms parameters in used in this study.

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Fig 11.

Results of training as well as validation: The matrix of confusion of all ML models.

(a) Stacking, (b) AdaBoost, (c) Bagging, (d) K-NN, (e) LR, (f) MLP, (g) RF, (h) SGD, (i) Voting, (j) XGBoost.

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Fig 12.

Confusion matrix and ROC curve of hybrid stacking model with binary classifications.

(a) Confusion Matrix, (b) ROC curve.

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Fig 13.

All ML models ROC curve over every class.

(a) Adaboost, (b) Bagging, (c) K-NN, (d) LR, (e) MLP, (f) RF, (g) SGD, (h) Voting, (i) XGBoost, (j) Stacking.

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Table 5.

All ML models AUC score list.

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Fig 14.

The collection of data assessment’s accuracy, precision, recall, and F1 score of all ML models.

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Table 6.

All ML models classification reports of precision, recall, F1 score, and accuracy.

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Fig 15.

Results of training as well as validation: The matrix of confusion of all ML models.

(a) BiGRU, (b) CLSTM, (c) CNN, (d) DNN, (e) RNN.

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Fig 16.

All DL models ROC curve over every class.

(a) BiGRU, (b) CLSTM, (c) CNN, (d) RNN, (e) DNN.

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Table 7.

AUC score comparison table for all the deep learning algorithms.

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Fig 17.

The collection of data assessment’s accuracy, precision, recall, and F1 score.

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Table 8.

All DL models classification report of precision, recall, F1 score and accuracy.

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Fig 18.

Classification report of proposed hybrid model.

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Table 9.

Comparison of the proposed model with previous investigations.

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Fig 19.

Web view of our system.

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