Argumentation Analysis (ArguAna) for the Web is a cooperative research project of the Webis group at the Bauhaus-Universität Weimar and the UKP lab at the TU Darmstadt, funded by the German Research Foundation (DFG).
The project targets at the specific challenges of mining arguments and their relations from natural language text on the web. We seek to establish foundations of algorithms that
- robustly apply to various forms of web argumentation,
- efficiently leverage the scale of the web, and
- complement argument mining with an argumentation analysis to effectively assess important quality dimensions.
The rationale of the project is that people compare arguments in many situations, e.g., when buying products or when forming opinions on political controversies. The richest and most up-to-date argument source is the web. Previous research on argument mining tackles the identification and relation of arguments within a particular domain, but it does not suffice to successfully mine arguments from the web.
As part of our research, we developed the following tools:
- Service: Argument search.
Search engine for arguments from the web.
- API: Argument search.
Access to the argument search engine via a REST interface.
- Demo: Essay scoring.
Assessing the Argumentation Quality of Persuasive Essays. Thanks to Patrick Saad for the nice demo!
- Henning Wachsmuth
- Benno Stein
- Yamen Ajjour
- Khalid Al-Khatib
- Wei-Fan Chen
- Johannes Kiesel
- Ivan Habernal @ TU Darmstadt
- Iryna Gurevych @ TU Darmstadt
Students: Janek Bevendorff, Jonas Dorsch, Viorel Morari, Jana Puschmann, Jiani Qu, Patrick Saad