CivX

CivX is an innovative project focused on detecting and mitigating cyberbullying through advanced machine learning models. As part of this initiative, we created a social media platform, CivX, where users can post images and interact by commenting on them.

The core functionality of CivX revolves around the analysis of comments and replies on these posts, using cutting-edge machine learning algorithms such as Chained LSTM and BERT. These models assess whether the comments contain cyberbullying content and, if so, classify the type of bullying, such as ethnic, age, or other categories.

In addition, the project incorporates bystander dynamics, which helps to understand the role of individuals who are not directly involved in the bullying but may influence the situation. This multi-faceted approach aims to not only detect harmful interactions but also provide insights into the broader social dynamics on online platforms.

I was responsible for completing the *Machine Learning* section of the project, where I developed, trained, and fine-tuned the models to effectively identify and classify cyberbullying content. This work was crucial in ensuring the accuracy and reliability of the system's predictions.

Credits
This project was a collaborative effort, and each team member played a crucial role in bringing CivX to life:

Shanis K – Led the Machine Learning module. Responsible for developing, training, and fine-tuning advanced ML models such as Chained LSTM and BERT for cyberbullying detection and classification, including bystander analysis.

Salman – Handled the entire Frontend and Backend development of the CivX platform. He built the user interface and managed the server-side logic, ensuring seamless integration of ML models and smooth user experience.

Sarang – Managed all Documentation work. He was responsible for preparing technical reports, project overviews, and ensuring the clarity and completeness of all written deliverables.