Examining Toxicity’s Impact on Reddit Conversations

Amidst the growth of harmful content on social media platforms, encompassing abusive language, disrespect, and hate speech, efforts to tackle this issue persist. However, effectively preventing the impact of such content on individuals and communities remains a challenging endeavor. In this paper, we present a study using Reddit data, where we employ a tree structure to visually and comprehensively examine the impact of toxic content on communities. By applying various machine learning algorithms, we classify the toxicity of each leaf node based on its parent and grandparent nodes, as well as the overall tree’s average toxicity. Our methodology can help policymakers detect early warning signs of toxicity and redirect potentially harmful comments to less toxic directions. Our research provides a comprehensive analysis of toxicity on social media platforms, allowing for a better understanding of differences and similarities across platforms, and a deeper exploration of the impact of toxic content on individual communities. Our findings provide valuable perspectives on the prevalence and consequences of toxic content on social media platforms, and our approach can be used in future studies to provide a more nuanced understanding of this complex issue.