Shekh Tanjil Sharif

A Multi-Platform Cyberbullying and Toxic Span Detection Dataset for Advanced NLP

Raihan Hossain, Lamia Syed, Shekh Tanjil Sharif

This dataset features 75,000 carefully curated and fully balanced social media textual records designed for cyberbullying classification and sequence-labeling toxic span detection. Collected and mapped across four distinct digital ecosystems—Facebook (FB), Instagram (IG), Reddit, and online News Portals—the corpus spans seven operational …

A Multi-Platform Cyberbullying and Toxic Span Detection Dataset for Advanced NLP

Raihan Hossain, Lamia Syed, Shekh Tanjil Sharif

This dataset features 75,000 carefully curated and fully balanced social media textual records designed for cyberbullying classification and sequence-labeling toxic span detection. Collected and mapped across four distinct digital ecosystems—Facebook (FB), Instagram (IG), Reddit, and online News Portals—the corpus spans seven operational …

Cyberbullying and Toxic Span Detection Dataset

Raihan Hossain, Lamia Syed, Shekh Tanjil Sharif

Sentiment, Emotion analysis for mental health based on text

Raihan Hossain, Lamia Syed, Shekh Tanjil Sharif, Ashikur Rahman Asif

This dataset contains 160,000 social media text records curated and customized from two distinct sources to facilitate advanced emotion recognition and sentiment analysis tasks. The text entries capture nuanced human emotions and psychological states expressed on digital platforms. Each record is categorized …

bd (code pays fourni par la source)

Sentiment, Emotion analysis for mental health based on text

Raihan Hossain, Lamia Syed, Shekh Tanjil Sharif, Ashikur Rahman Asif

This dataset contains 160,000 social media text records curated and customized from two distinct sources to facilitate advanced emotion recognition and sentiment analysis tasks. The text entries capture nuanced human emotions and psychological states expressed on digital platforms. Each record is categorized …

bd (code pays fourni par la source)

Sentiment, Emotion analysis for mental health based on text

Raihan Hossain, Lamia Syed, Shekh Tanjil Sharif, Ashikur Rahman Asif

This dataset contains 160,000 social media text records curated and customized from two distinct sources to facilitate advanced emotion recognition and sentiment analysis tasks. The text entries capture nuanced human emotions and psychological states expressed on digital platforms. Each record is categorized …

bd (code pays fourni par la source)

Evaluating and Mitigating Bias in Loan Approval Systems: A Multi-Model Empirical Study Using Fairness Metrics and Post-Processing Techniques

Ashikur Rahman Asif, Homayra Zohor Oitizzo, Shekh Tanjil Sharif, Md. Raihan Hossain et autres

Though automated loan approval systems based on machine learning offer effective results, can turn up demographic bias inherent in historical data. This study is a fairness-aware evaluation framework which works for binary loan approval that examines predictive performance, algorithmic fairness, and model …

bd (code pays fourni par la source)

Text-Based Mental Health Detection Using Stacking Ensemble Approach with Hybrid Machine Learning and Deep Learning Models

Md. Raihan Hossain, Lamia Syed, Shekh Tanjil Sharif, Ashikur Rahman Asif et autres

The growing prevalence of mental health disorders demands reliable and scalable automated detection systems. This work introduces a hybrid ensemble framework that combines context-aware transformers (RoBERTa) with BiLSTM-based sequential learning and an XGBoost metaclassifier for robust mental health classification. Experiments conducted on …

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Deep Learning-Based Recognition of Bangla Sign Language Gestures with CNN, VGG16, and MobileNetV2

Rabab Khan Rongon, Muhammad Shahriar Zaman, Shekh Tanjil Sharif, Sadab Khan Prangon et autres

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Proposing and Evaluating a new CAPTCHA Systems for Improving Usability and Accessibility

Rabab Khan Rongon, Anika Ashraf, Shekh Tanjil Sharif, Muhammad Nazrul Islam

Traditional CAPTCHA systems can block automated bots, but they often create problems for elderly people and users with visual or cognitive difficulties. This study introduces a new dual-layer CAPTCHA model to solve these issues and make human verification more inclusive. The system …

bd (code pays fourni par la source)