Cyberbullying Classification

Cyberbullying is a form of online harassment that can have severe psychological and emotional effects on the victim. It can include posting hurtful messages, sharing private information, and making threatening comments.

Highlighting the topic of cyberbullying is essential because it raises awareness about this growing problem and its harmful impact on individuals and society.

This project explores data representations for building effective and impactful visualizations of data stories. By collecting and manipulating a large quantity of data, I have created a visualization that emphasizes the visual form and how it dialogues with its informational and cultural contexts. Given the complexity and size of the dataset, I have applied computational methods to create the visualization.

What is the Purpose?

Creating a multiclassification visualization to understand the cyberbullying type that can help identify the patterns and trends related to cyberbullying behavior on Twitter. By analyzing the language, sentiment, and context of tweets, researchers and practitioners can gain insights into the nature of cyberbullying incidents.

Exploring the words and patterns associated with each type of cyberbullying. This can help raise awareness of cyberbullying and its impact on individuals and communities. Presenting the data in a visually appealing way can help to engage audiences and promote understanding of the issue.

Who is the target audience?

Educators and school administrators who want to promote a safe and respectful online environment for their students need resources and strategies for addressing cyberbullying in schools.

Mental health professionals who work with individuals who have been affected by cyberbullying need to understand the psychological and emotional impact of online harassment.

Social media companies and policymakers who want to create policies and initiatives to prevent cyberbullying and promote positive online behavior.

Dataset

As social media usage becomes increasingly prevalent in every age group, a vast majority of citizens rely on this essential medium for day-to-day communication. Cyberbullying can effectively impact anyone at any time or anywhere, and due to the anonymity of the internet, such attacks take place quite often.

The dataset contains more than 47000 tweets labeled according to the class of cyberbullying: Age, Gender, Ethnicity, Religion, and other hate.

Source: Kaggle.com | Click here to download the CSV file

Stage One

Using Processing tool I have mapped the dataset without aggregating any data. The idea was to have a straightforward, direct, visual dump of the data onto a static canvas and visualize it as an uninterrupted visual pattern.

Stage Two

This stage involved creating a static dashboard in a single panel that described the data. The iteration consists of wordclouds, boxplot, etc. with special attention given to the typography, layout, hierarchy, and color scheme.

Stage Three

In the concluding phase, a singular static frame was crafted to distinctly convey the primary message concerning cyberbullying, ensuring clarity and explicit communication.

Disclaimer

This project includes visual representations, such as word clouds, generated from a dataset focused on cyberbullying that is sourced from Twitter. The content displayed may contain explicit language, and abusive expressions. The primary purpose is to illustrate the harsh realities faced by individuals and communities affected by online harassment. The intention is not to endorse or promote harmful language but to shed light on the importance of addressing online abuse.