This project uses Natural Language Processing (NLP) to analyze tweets and predict whether they contain cyberbullying content. It categorizes cyberbullying into six categories: Age, Ethnicity, Gender, Religion, Other Cyberbullying.

Cyberbullying Detection App using BERT NLP and Streamlit

Capstone Project for Data Science Program at Flatiron School. Using Natural Language Processing (NLP) to predict whether or not a post contains cyberbullying (hate speech) so that it can be filtered or prevented before causing harm.

Cyber Bully Detection System is an AI-powered system that uses NLP to detect and prevent cyberbullying in online spaces. By combining synthetic training data with real-world testing, it aims to create safer, more respectful digital interactions.

Analyzing cyberbullying behavior in social media using Supervised Machine Learning algorithms and Natural Language Processing (NLP)

NLP-based machine learning system for detecting and classifying cyberbullying in text data using supervised learning and text processing techniques.

An AI-powered cyberbullying classification system that detects abusive, threatening, and harmful language in online messages. Uses NLP techniques for text classification, sentiment analysis, and automated moderation to enhance online safety

Cyberbullying Detection Using NLP and Deep Learning

analyzing cyberbullying tweets from twitter using NLP

tackles cyberbullying detection on Twitter using NLP for binary classification.

No description available

No description available

prevention of cyberbullying using machine learning algorithms / using python , sklearn and NLP (NLTK)

No description available

X_Cyberbullying is a machine learning model designed to predict and detect cyberbullying in textual content. This project focuses on using NLP techniques to analyze text data and classify it as either cyberbullying or non-cyberbullying.

Cyberbullying Tweet Predictor using NLP and Flask. Project for CBSE-Intel AI For Youth Bootcamp on Natural Language Processing.

KindSpeack is an AI-powered system designed to detect cyberbullying in social media messages using Natural Language Processing (NLP)

Classifying tweets using NLP to determine if they are a subclass of cyberbullying (e.g. gender, religion) or not.

Developed a machine learning model using NLP techniques to detect sentiment patterns and early signs of cyberbullying in tweets

AI-powered cyberbullying detection web app using NLP and machine learning that analyzes text and identifies harmful or toxic language in real time.

NLP-based cyberbullying detection system achieving 82.4% accuracy across 6 categories. Features real-time classification using Logistic Regression and TF-IDF vectorization.

This GitHub repository houses a powerful project that addresses cyberbullying by leveraging Python, NLP (Natural Language Processing), and fine-tuned SVM (Support Vector Machine) classification. Using the Twitter API, the project collects and analyzes tweets to identify and flag cyberbullying content.

Machine learning project for cyberbullying detection using NLP techniques and scikit-learn. Includes text preprocessing, TF-IDF feature extraction, Logistic Regression model, and evaluation with classification metrics.

Detect cyberbullying in tweets using NLP and Deep Learning (Bi-LSTM). This project includes data preprocessing, tokenization, model training, evaluation, and real-time prediction. Built with Python, TensorFlow, and NLTK. Ideal for ML/NLP beginners & final year projects.

An end‑to‑end NLP system for detecting cyberbullying in Telugu social media comments using BERT‑based transformer models, with support for Telugu script, Tenglish, and code‑mixed Telugu–English text.

HTDM (Hyper Threat Detection Model): AI system detecting digital threats across text, images, and videos. Predicts fake news, cyberbullying, and deepfake content using multi-modal ML/NLP techniques. Lightweight, accurate, and ready for real-time deployment.

A dual-mode Cyberbullying Detection system using NLP and ML that classifies comments as offensive or non-offensive for both Gen-Z and Millennial language patterns. Built with Python, Flask, and deep learning embeddings for sarcasm-aware text classification.

This project focuses on detecting cyberbullying content on social media platforms using Machine Learning and Natural Language Processing (NLP) techniques. The system analyzes user-generated text and classifies it as bullying or non-bullying, helping in automated content moderation and online safety.

KindSpeack is an AI-powered system designed to detect cyberbullying in social media messages using Natural Language Processing (NLP)

Cyberbullying Detector using NLP