ArticleScientific reports2022
Multi-class sentiment analysis of urdu text using multilingual BERT.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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17 citing papers in PubMed.
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- The usage of artificial Intelligence-empowered text analysis model with convolutional neural network in english reading.Scientific reports · 2025Article
- A Language model-based approach to sentiment classification of languages in central Asia.Scientific reports · 2025Article
- Ensemble stacked model for enhanced identification of sentiments from IMDB reviews.Scientific reports · 2025Article
- Sentiment mining of online comments of sports venues: Consumer satisfaction and its influencing factors.PloS one · 2025Article
- Evolving techniques in sentiment analysis: a comprehensive review.PeerJ. Computer science · 2025Article
- Cword2vec: a novel morphological rule-based word embedding approach for Urdu text sentiment analysis.PeerJ. Computer science · 2025Article
- Heart disease prediction using hybrid TabNet architecture with stacked ensemble learning.Frontiers in physiology · 2025Article
- Dynamic emotion recognition and learning motivation prediction in Chinese second language acquisition under cultural differences: a study based on ED-CM-MP model.Frontiers in psychology · 2025Article
- Roman urdu hate speech detection using hybrid machine learning models and hyperparameter optimization.Scientific reports · 2024Article
- Migraine headache (MH) classification using machine learning methods with data augmentation.Scientific reports · 2024Article
- Sentiment analysis of COP9-related tweets: a comparative study of pre-trained models and traditional techniques.Frontiers in big data · 2024Article
- A hybrid dependency-based approach for Urdu sentiment analysis.Scientific reports · 2023Article
- Correcting spelling mistakes in Persian texts with rules and deep learning methods.Scientific reports · 2023Article
- Short text classification approach to identify child sexual exploitation material.Scientific reports · 2023Article
- Roman Urdu Hate Speech Detection Using Transformer-Based Model for Cyber Security Applications.Sensors (Basel, Switzerland) · 2023Article
- Data augmentation and deep neural networks for the classification of Pakistani racial speakers recognition.PeerJ. Computer science · 2022Article
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4 authors.
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Abstract
Sentiment analysis (SA) is an important task because of its vital role in analyzing people's opinions. However, existing research is solely based on the English language with limited work on low-resource languages. This study introduced a new multi-class Urdu dataset based on user reviews for sentiment analysis. This dataset is gathered from various domains such as food and beverages, movies and plays, software and apps, politics, and sports. Our proposed dataset contains 9312 reviews manually annotated by human experts into three classes: positive, negative and neutral. The main goal of this research study is to create a manually annotated dataset for Urdu sentiment analysis and to set baseline results using rule-based, machine learning (SVM, NB, Adabbost, MLP, LR and RF) and deep learning (CNN-1D, LSTM, Bi-LSTM, GRU and Bi-GRU) techniques. Additionally, we fine-tuned Multilingual BERT(mBERT) for Urdu sentiment analysis. We used four text representations: word n-grams, char n-grams,pre-trained fastText and BERT word embeddings to train our classifiers. We trained these models on two different datasets for evaluation purposes. Finding shows that the proposed mBERT model with BERT pre-trained word embeddings outperformed deep learning, machine learning and rule-based classifiers and achieved an F1 score of 81.49%.
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