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Cyberbullying Detection using NLP

Project Overview

This project aims to detect instances of cyberbullying in social media posts using Natural Language Processing (NLP) techniques. Given the increasing prevalence of cyberbullying and its harmful impact, developing effective tools for automatic detection is crucial for creating safer online environments.

Objectives

  • Develop an NLP-based model to identify cyberbullying in social media posts.

  • Contribute to the prevention and mitigation of online harassment by providing a tool for automatic content moderation.

Data Collection

Data for this project is sourced from Kaggle, consisting of labeled social media posts specifically curated for cyberbullying detection tasks.

Project Stages

  • Data Preprocessing: Cleaning and preparing the text data.

  • Exploratory Data Analysis (EDA): Analyzing the dataset to uncover insights.

  • Model Selection: Choosing suitable machine learning models.

  • Model Training: Training the selected models.

  • Model Evaluation: Assessing the models' performance using various metrics.