ArgumenText allows searching large document collections for arguments. In response to a user-defined topic, our technology determines relevant pro and con arguments in real-time, and presents them as a concise summary. Arguments can also be grouped by subtopic automatically. Decision-relevant information can be found much faster and complex decision-making processes can be significantly improved by exploiting the potential of large text collections. Applied to text streams like news streams or social media, latest trends and innovations can be discovered with ease.
Our demonstrator illustrates the potential of argument mining to extract arguments on any topic from any web source. It shows how arguments mined from heterogeneous sources can be grouped in argumentative pro and con facets to obtain a concise summary of nascent debates. By maintaining the links to the source documents, each of the found representants can be analyzed in more detail to receive a comprehensive overview of the controversy.