Cyberbullying Dataset using ML

Keywords: Cyberbullying,prediction,machine learning

Background

Cyberbullying has become a pervasive issue in today's digital age, with detrimental effects on individuals' mental and emotional well-being. As a result, there is a growing need for effective automated tools to detect and combat cyberbullying instances on various online platforms. This abstract introduces an annotated cyberbullying dataset curated specifically for advancing machine learning research in the field of cyberbullying detection and prevention. The dataset comprises a diverse collection of text data extracted from social media platforms, online forums, and other web sources where cyberbullying incidents commonly occur. The dataset includes a wide range of cyberbullying scenarios, such as personal attacks, hate speech, body shaming, and other forms of harmful online interactions. The text data is accompanied by annotations that indicate whether a given instance constitutes cyberbullying, as well as additional labels specifying the type or category of cyberbullying behavior exhibited

Aim & Objectives

Aim
The main of this project is predicting the cyberbullying tweets using NLP
Objective
• Loading the dataset
• Cleaning and pre-processing
• Outlier imputation using required methods
• Data Visualization and Statistical testing’s
• Building the machine learning model

Research Methodology

NLP and Various Classification Algorithms

Software & Tools

Jupyter, Google Collab

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