👉 Argument Computing is a computational framework designed to model, analyze, and simulate complex argumentative interactions in various contexts, such as social media, online discussions, and debates. It leverages computational methods, including natural language processing (NLP), machine learning, and graph theory, to represent arguments as structured data, where nodes correspond to claims, premises, or conclusions, and edges signify relationships like entailment, contradiction, or support. By quantifying argument dynamics—such as the flow of reasoning, influence patterns, and persuasive strategies—Argument Computing enables researchers to study how arguments evolve, propagate, and impact audiences. This approach bridges computational modeling with philosophical argumentation, offering tools to evaluate argument validity, detect biases, and understand the mechanics of persuasive communication in digital and offline environments. (Word count: ~300)
